diff --git a/Documentation/doxygen.conf.in b/Documentation/doxygen.conf.in
index 9894e91259..f18f492edf 100644
--- a/Documentation/doxygen.conf.in
+++ b/Documentation/doxygen.conf.in
@@ -1,1928 +1,1928 @@
# Doxyfile 1.8.0
# This file describes the settings to be used by the documentation system
# doxygen (www.doxygen.org) for a project.
#
# All text after a hash (#) is considered a comment and will be ignored.
# The format is:
# TAG = value [value, ...]
# For lists items can also be appended using:
# TAG += value [value, ...]
# Values that contain spaces should be placed between quotes (" ").
#---------------------------------------------------------------------------
# Project related configuration options
#---------------------------------------------------------------------------
# This tag specifies the encoding used for all characters in the config file
# that follow. The default is UTF-8 which is also the encoding used for all
# text before the first occurrence of this tag. Doxygen uses libiconv (or the
# iconv built into libc) for the transcoding. See
# http://www.gnu.org/software/libiconv for the list of possible encodings.
DOXYFILE_ENCODING = UTF-8
# The PROJECT_NAME tag is a single word (or sequence of words) that should
# identify the project. Note that if you do not use Doxywizard you need
# to put quotes around the project name if it contains spaces.
PROJECT_NAME = MITK
# The PROJECT_NUMBER tag can be used to enter a project or revision number.
# This could be handy for archiving the generated documentation or
# if some version control system is used.
PROJECT_NUMBER = @MITK_VERSION_STRING@
# Using the PROJECT_BRIEF tag one can provide an optional one line description
# for a project that appears at the top of each page and should give viewer
# a quick idea about the purpose of the project. Keep the description short.
PROJECT_BRIEF = "Medical Imaging Interaction Toolkit"
# With the PROJECT_LOGO tag one can specify an logo or icon that is
# included in the documentation. The maximum height of the logo should not
# exceed 55 pixels and the maximum width should not exceed 200 pixels.
# Doxygen will copy the logo to the output directory.
PROJECT_LOGO =
# The OUTPUT_DIRECTORY tag is used to specify the (relative or absolute)
# base path where the generated documentation will be put.
# If a relative path is entered, it will be relative to the location
# where doxygen was started. If left blank the current directory will be used.
OUTPUT_DIRECTORY = @MITK_DOXYGEN_OUTPUT_DIR@
# If the CREATE_SUBDIRS tag is set to YES, then doxygen will create
# 4096 sub-directories (in 2 levels) under the output directory of each output
# format and will distribute the generated files over these directories.
# Enabling this option can be useful when feeding doxygen a huge amount of
# source files, where putting all generated files in the same directory would
# otherwise cause performance problems for the file system.
CREATE_SUBDIRS = NO
# The OUTPUT_LANGUAGE tag is used to specify the language in which all
# documentation generated by doxygen is written. Doxygen will use this
# information to generate all constant output in the proper language.
# The default language is English, other supported languages are:
# Afrikaans, Arabic, Brazilian, Catalan, Chinese, Chinese-Traditional,
# Croatian, Czech, Danish, Dutch, Esperanto, Farsi, Finnish, French, German,
# Greek, Hungarian, Italian, Japanese, Japanese-en (Japanese with English
# messages), Korean, Korean-en, Lithuanian, Norwegian, Macedonian, Persian,
# Polish, Portuguese, Romanian, Russian, Serbian, Serbian-Cyrillic, Slovak,
# Slovene, Spanish, Swedish, Ukrainian, and Vietnamese.
OUTPUT_LANGUAGE = English
# If the BRIEF_MEMBER_DESC tag is set to YES (the default) Doxygen will
# include brief member descriptions after the members that are listed in
# the file and class documentation (similar to JavaDoc).
# Set to NO to disable this.
BRIEF_MEMBER_DESC = YES
# If the REPEAT_BRIEF tag is set to YES (the default) Doxygen will prepend
# the brief description of a member or function before the detailed description.
# Note: if both HIDE_UNDOC_MEMBERS and BRIEF_MEMBER_DESC are set to NO, the
# brief descriptions will be completely suppressed.
REPEAT_BRIEF = YES
# This tag implements a quasi-intelligent brief description abbreviator
# that is used to form the text in various listings. Each string
# in this list, if found as the leading text of the brief description, will be
# stripped from the text and the result after processing the whole list, is
# used as the annotated text. Otherwise, the brief description is used as-is.
# If left blank, the following values are used ("$name" is automatically
# replaced with the name of the entity): "The $name class" "The $name widget"
# "The $name file" "is" "provides" "specifies" "contains"
# "represents" "a" "an" "the"
ABBREVIATE_BRIEF =
# If the ALWAYS_DETAILED_SEC and REPEAT_BRIEF tags are both set to YES then
# Doxygen will generate a detailed section even if there is only a brief
# description.
ALWAYS_DETAILED_SEC = NO
# If the INLINE_INHERITED_MEMB tag is set to YES, doxygen will show all
# inherited members of a class in the documentation of that class as if those
# members were ordinary class members. Constructors, destructors and assignment
# operators of the base classes will not be shown.
INLINE_INHERITED_MEMB = NO
# If the FULL_PATH_NAMES tag is set to YES then Doxygen will prepend the full
# path before files name in the file list and in the header files. If set
# to NO the shortest path that makes the file name unique will be used.
FULL_PATH_NAMES = NO
# If the FULL_PATH_NAMES tag is set to YES then the STRIP_FROM_PATH tag
# can be used to strip a user-defined part of the path. Stripping is
# only done if one of the specified strings matches the left-hand part of
# the path. The tag can be used to show relative paths in the file list.
# If left blank the directory from which doxygen is run is used as the
# path to strip.
STRIP_FROM_PATH =
# The STRIP_FROM_INC_PATH tag can be used to strip a user-defined part of
# the path mentioned in the documentation of a class, which tells
# the reader which header file to include in order to use a class.
# If left blank only the name of the header file containing the class
# definition is used. Otherwise one should specify the include paths that
# are normally passed to the compiler using the -I flag.
STRIP_FROM_INC_PATH =
# If the SHORT_NAMES tag is set to YES, doxygen will generate much shorter
# (but less readable) file names. This can be useful if your file system
# doesn't support long names like on DOS, Mac, or CD-ROM.
SHORT_NAMES = NO
# If the JAVADOC_AUTOBRIEF tag is set to YES then Doxygen
# will interpret the first line (until the first dot) of a JavaDoc-style
# comment as the brief description. If set to NO, the JavaDoc
# comments will behave just like regular Qt-style comments
# (thus requiring an explicit @brief command for a brief description.)
JAVADOC_AUTOBRIEF = NO
# If the QT_AUTOBRIEF tag is set to YES then Doxygen will
# interpret the first line (until the first dot) of a Qt-style
# comment as the brief description. If set to NO, the comments
# will behave just like regular Qt-style comments (thus requiring
# an explicit \brief command for a brief description.)
QT_AUTOBRIEF = NO
# The MULTILINE_CPP_IS_BRIEF tag can be set to YES to make Doxygen
# treat a multi-line C++ special comment block (i.e. a block of //! or ///
# comments) as a brief description. This used to be the default behaviour.
# The new default is to treat a multi-line C++ comment block as a detailed
# description. Set this tag to YES if you prefer the old behaviour instead.
MULTILINE_CPP_IS_BRIEF = NO
# If the INHERIT_DOCS tag is set to YES (the default) then an undocumented
# member inherits the documentation from any documented member that it
# re-implements.
INHERIT_DOCS = YES
# If the SEPARATE_MEMBER_PAGES tag is set to YES, then doxygen will produce
# a new page for each member. If set to NO, the documentation of a member will
# be part of the file/class/namespace that contains it.
SEPARATE_MEMBER_PAGES = NO
# The TAB_SIZE tag can be used to set the number of spaces in a tab.
# Doxygen uses this value to replace tabs by spaces in code fragments.
TAB_SIZE = 8
# This tag can be used to specify a number of aliases that acts
# as commands in the documentation. An alias has the form "name=value".
# For example adding "sideeffect=\par Side Effects:\n" will allow you to
# put the command \sideeffect (or @sideeffect) in the documentation, which
# will result in a user-defined paragraph with heading "Side Effects:".
# You can put \n's in the value part of an alias to insert newlines.
ALIASES = "FIXME=\par Fix Me's:\n" \
"BlueBerry=\if BLUEBERRY" \
"endBlueBerry=\endif" \
"bundlemainpage{1}=\page \1" \
"embmainpage{1}=\page \1" \
"github{2}=\2" \
"deprecatedSince{1}=\xrefitem deprecatedSince\1 \" Deprecated as of \1\" \"Functions deprecated as of \1\" " \
"minimumCMakeVersion=@CMAKE_MINIMUM_REQUIRED_VERSION@" \
"minimumQt4Version=@MITK_QT4_MINIMUM_VERSION@" \
"imageMacro{3}=\image html \1 \2 \n \image latex \1 \2 width=\3cm" \
"developersguidemainpage{1}=\page \1 " \
"usersguidemainpage{1}=\page \1 " \
"nondependentPluginLink{3}= \ref \1 \"\3\" "
# This tag can be used to specify a number of word-keyword mappings (TCL only).
# A mapping has the form "name=value". For example adding
# "class=itcl::class" will allow you to use the command class in the
# itcl::class meaning.
TCL_SUBST =
# Set the OPTIMIZE_OUTPUT_FOR_C tag to YES if your project consists of C
# sources only. Doxygen will then generate output that is more tailored for C.
# For instance, some of the names that are used will be different. The list
# of all members will be omitted, etc.
OPTIMIZE_OUTPUT_FOR_C = NO
# Set the OPTIMIZE_OUTPUT_JAVA tag to YES if your project consists of Java
# sources only. Doxygen will then generate output that is more tailored for
# Java. For instance, namespaces will be presented as packages, qualified
# scopes will look different, etc.
OPTIMIZE_OUTPUT_JAVA = NO
# Set the OPTIMIZE_FOR_FORTRAN tag to YES if your project consists of Fortran
# sources only. Doxygen will then generate output that is more tailored for
# Fortran.
OPTIMIZE_FOR_FORTRAN = NO
# Set the OPTIMIZE_OUTPUT_VHDL tag to YES if your project consists of VHDL
# sources. Doxygen will then generate output that is tailored for
# VHDL.
OPTIMIZE_OUTPUT_VHDL = NO
# Doxygen selects the parser to use depending on the extension of the files it
# parses. With this tag you can assign which parser to use for a given extension.
# Doxygen has a built-in mapping, but you can override or extend it using this
# tag. The format is ext=language, where ext is a file extension, and language
# is one of the parsers supported by doxygen: IDL, Java, Javascript, CSharp, C,
# C++, D, PHP, Objective-C, Python, Fortran, VHDL, C, C++. For instance to make
# doxygen treat .inc files as Fortran files (default is PHP), and .f files as C
# (default is Fortran), use: inc=Fortran f=C. Note that for custom extensions
# you also need to set FILE_PATTERNS otherwise the files are not read by doxygen.
EXTENSION_MAPPING =
# If MARKDOWN_SUPPORT is enabled (the default) then doxygen pre-processes all
# comments according to the Markdown format, which allows for more readable
# documentation. See http://daringfireball.net/projects/markdown/ for details.
# The output of markdown processing is further processed by doxygen, so you
# can mix doxygen, HTML, and XML commands with Markdown formatting.
# Disable only in case of backward compatibilities issues.
MARKDOWN_SUPPORT = YES
# If you use STL classes (i.e. std::string, std::vector, etc.) but do not want
# to include (a tag file for) the STL sources as input, then you should
# set this tag to YES in order to let doxygen match functions declarations and
# definitions whose arguments contain STL classes (e.g. func(std::string); v.s.
# func(std::string) {}). This also makes the inheritance and collaboration
# diagrams that involve STL classes more complete and accurate.
BUILTIN_STL_SUPPORT = YES
# If you use Microsoft's C++/CLI language, you should set this option to YES to
# enable parsing support.
CPP_CLI_SUPPORT = NO
# Set the SIP_SUPPORT tag to YES if your project consists of sip sources only.
# Doxygen will parse them like normal C++ but will assume all classes use public
# instead of private inheritance when no explicit protection keyword is present.
SIP_SUPPORT = NO
# For Microsoft's IDL there are propget and propput attributes to indicate getter
# and setter methods for a property. Setting this option to YES (the default)
# will make doxygen replace the get and set methods by a property in the
# documentation. This will only work if the methods are indeed getting or
# setting a simple type. If this is not the case, or you want to show the
# methods anyway, you should set this option to NO.
IDL_PROPERTY_SUPPORT = YES
# If member grouping is used in the documentation and the DISTRIBUTE_GROUP_DOC
# tag is set to YES, then doxygen will reuse the documentation of the first
# member in the group (if any) for the other members of the group. By default
# all members of a group must be documented explicitly.
DISTRIBUTE_GROUP_DOC = YES
# Set the SUBGROUPING tag to YES (the default) to allow class member groups of
# the same type (for instance a group of public functions) to be put as a
# subgroup of that type (e.g. under the Public Functions section). Set it to
# NO to prevent subgrouping. Alternatively, this can be done per class using
# the \nosubgrouping command.
SUBGROUPING = YES
# When the INLINE_GROUPED_CLASSES tag is set to YES, classes, structs and
# unions are shown inside the group in which they are included (e.g. using
# @ingroup) instead of on a separate page (for HTML and Man pages) or
# section (for LaTeX and RTF).
INLINE_GROUPED_CLASSES = NO
# When the INLINE_SIMPLE_STRUCTS tag is set to YES, structs, classes, and
# unions with only public data fields will be shown inline in the documentation
# of the scope in which they are defined (i.e. file, namespace, or group
# documentation), provided this scope is documented. If set to NO (the default),
# structs, classes, and unions are shown on a separate page (for HTML and Man
# pages) or section (for LaTeX and RTF).
INLINE_SIMPLE_STRUCTS = NO
# When TYPEDEF_HIDES_STRUCT is enabled, a typedef of a struct, union, or enum
# is documented as struct, union, or enum with the name of the typedef. So
# typedef struct TypeS {} TypeT, will appear in the documentation as a struct
# with name TypeT. When disabled the typedef will appear as a member of a file,
# namespace, or class. And the struct will be named TypeS. This can typically
# be useful for C code in case the coding convention dictates that all compound
# types are typedef'ed and only the typedef is referenced, never the tag name.
TYPEDEF_HIDES_STRUCT = NO
# The SYMBOL_CACHE_SIZE determines the size of the internal cache use to
# determine which symbols to keep in memory and which to flush to disk.
# When the cache is full, less often used symbols will be written to disk.
# For small to medium size projects (<1000 input files) the default value is
# probably good enough. For larger projects a too small cache size can cause
# doxygen to be busy swapping symbols to and from disk most of the time
# causing a significant performance penalty.
# If the system has enough physical memory increasing the cache will improve the
# performance by keeping more symbols in memory. Note that the value works on
# a logarithmic scale so increasing the size by one will roughly double the
# memory usage. The cache size is given by this formula:
# 2^(16+SYMBOL_CACHE_SIZE). The valid range is 0..9, the default is 0,
# corresponding to a cache size of 2^16 = 65536 symbols.
SYMBOL_CACHE_SIZE = 0
# Similar to the SYMBOL_CACHE_SIZE the size of the symbol lookup cache can be
# set using LOOKUP_CACHE_SIZE. This cache is used to resolve symbols given
# their name and scope. Since this can be an expensive process and often the
# same symbol appear multiple times in the code, doxygen keeps a cache of
# pre-resolved symbols. If the cache is too small doxygen will become slower.
# If the cache is too large, memory is wasted. The cache size is given by this
# formula: 2^(16+LOOKUP_CACHE_SIZE). The valid range is 0..9, the default is 0,
# corresponding to a cache size of 2^16 = 65536 symbols.
LOOKUP_CACHE_SIZE = 0
#---------------------------------------------------------------------------
# Build related configuration options
#---------------------------------------------------------------------------
# If the EXTRACT_ALL tag is set to YES doxygen will assume all entities in
# documentation are documented, even if no documentation was available.
# Private class members and static file members will be hidden unless
# the EXTRACT_PRIVATE and EXTRACT_STATIC tags are set to YES
EXTRACT_ALL = YES
# If the EXTRACT_PRIVATE tag is set to YES all private members of a class
# will be included in the documentation.
EXTRACT_PRIVATE = NO
# If the EXTRACT_PACKAGE tag is set to YES all members with package or internal scope will be included in the documentation.
EXTRACT_PACKAGE = NO
# If the EXTRACT_STATIC tag is set to YES all static members of a file
# will be included in the documentation.
EXTRACT_STATIC = YES
# If the EXTRACT_LOCAL_CLASSES tag is set to YES classes (and structs)
# defined locally in source files will be included in the documentation.
# If set to NO only classes defined in header files are included.
EXTRACT_LOCAL_CLASSES = @MITK_DOXYGEN_INTERNAL_DOCS@
# This flag is only useful for Objective-C code. When set to YES local
# methods, which are defined in the implementation section but not in
# the interface are included in the documentation.
# If set to NO (the default) only methods in the interface are included.
EXTRACT_LOCAL_METHODS = NO
# If this flag is set to YES, the members of anonymous namespaces will be
# extracted and appear in the documentation as a namespace called
# 'anonymous_namespace{file}', where file will be replaced with the base
# name of the file that contains the anonymous namespace. By default
# anonymous namespaces are hidden.
EXTRACT_ANON_NSPACES = NO
# If the HIDE_UNDOC_MEMBERS tag is set to YES, Doxygen will hide all
# undocumented members of documented classes, files or namespaces.
# If set to NO (the default) these members will be included in the
# various overviews, but no documentation section is generated.
# This option has no effect if EXTRACT_ALL is enabled.
HIDE_UNDOC_MEMBERS = NO
# If the HIDE_UNDOC_CLASSES tag is set to YES, Doxygen will hide all
# undocumented classes that are normally visible in the class hierarchy.
# If set to NO (the default) these classes will be included in the various
# overviews. This option has no effect if EXTRACT_ALL is enabled.
HIDE_UNDOC_CLASSES = NO
# If the HIDE_FRIEND_COMPOUNDS tag is set to YES, Doxygen will hide all
# friend (class|struct|union) declarations.
# If set to NO (the default) these declarations will be included in the
# documentation.
HIDE_FRIEND_COMPOUNDS = @MITK_DOXYGEN_HIDE_FRIEND_COMPOUNDS@
# If the HIDE_IN_BODY_DOCS tag is set to YES, Doxygen will hide any
# documentation blocks found inside the body of a function.
# If set to NO (the default) these blocks will be appended to the
# function's detailed documentation block.
HIDE_IN_BODY_DOCS = NO
# The INTERNAL_DOCS tag determines if documentation
# that is typed after a \internal command is included. If the tag is set
# to NO (the default) then the documentation will be excluded.
# Set it to YES to include the internal documentation.
INTERNAL_DOCS = @MITK_DOXYGEN_INTERNAL_DOCS@
# If the CASE_SENSE_NAMES tag is set to NO then Doxygen will only generate
# file names in lower-case letters. If set to YES upper-case letters are also
# allowed. This is useful if you have classes or files whose names only differ
# in case and if your file system supports case sensitive file names. Windows
# and Mac users are advised to set this option to NO.
CASE_SENSE_NAMES = YES
# If the HIDE_SCOPE_NAMES tag is set to NO (the default) then Doxygen
# will show members with their full class and namespace scopes in the
# documentation. If set to YES the scope will be hidden.
HIDE_SCOPE_NAMES = NO
# If the SHOW_INCLUDE_FILES tag is set to YES (the default) then Doxygen
# will put a list of the files that are included by a file in the documentation
# of that file.
SHOW_INCLUDE_FILES = YES
# If the FORCE_LOCAL_INCLUDES tag is set to YES then Doxygen
# will list include files with double quotes in the documentation
# rather than with sharp brackets.
FORCE_LOCAL_INCLUDES = NO
# If the INLINE_INFO tag is set to YES (the default) then a tag [inline]
# is inserted in the documentation for inline members.
INLINE_INFO = YES
# If the SORT_MEMBER_DOCS tag is set to YES (the default) then doxygen
# will sort the (detailed) documentation of file and class members
# alphabetically by member name. If set to NO the members will appear in
# declaration order.
SORT_MEMBER_DOCS = YES
# If the SORT_BRIEF_DOCS tag is set to YES then doxygen will sort the
# brief documentation of file, namespace and class members alphabetically
# by member name. If set to NO (the default) the members will appear in
# declaration order.
SORT_BRIEF_DOCS = NO
# If the SORT_MEMBERS_CTORS_1ST tag is set to YES then doxygen
# will sort the (brief and detailed) documentation of class members so that
# constructors and destructors are listed first. If set to NO (the default)
# the constructors will appear in the respective orders defined by
# SORT_MEMBER_DOCS and SORT_BRIEF_DOCS.
# This tag will be ignored for brief docs if SORT_BRIEF_DOCS is set to NO
# and ignored for detailed docs if SORT_MEMBER_DOCS is set to NO.
SORT_MEMBERS_CTORS_1ST = NO
# If the SORT_GROUP_NAMES tag is set to YES then doxygen will sort the
# hierarchy of group names into alphabetical order. If set to NO (the default)
# the group names will appear in their defined order.
SORT_GROUP_NAMES = NO
# If the SORT_BY_SCOPE_NAME tag is set to YES, the class list will be
# sorted by fully-qualified names, including namespaces. If set to
# NO (the default), the class list will be sorted only by class name,
# not including the namespace part.
# Note: This option is not very useful if HIDE_SCOPE_NAMES is set to YES.
# Note: This option applies only to the class list, not to the
# alphabetical list.
SORT_BY_SCOPE_NAME = YES
# If the STRICT_PROTO_MATCHING option is enabled and doxygen fails to
# do proper type resolution of all parameters of a function it will reject a
# match between the prototype and the implementation of a member function even
# if there is only one candidate or it is obvious which candidate to choose
# by doing a simple string match. By disabling STRICT_PROTO_MATCHING doxygen
# will still accept a match between prototype and implementation in such cases.
STRICT_PROTO_MATCHING = NO
# The GENERATE_TODOLIST tag can be used to enable (YES) or
# disable (NO) the todo list. This list is created by putting \todo
# commands in the documentation.
GENERATE_TODOLIST = @MITK_DOXYGEN_GENERATE_TODOLIST@
# The GENERATE_TESTLIST tag can be used to enable (YES) or
# disable (NO) the test list. This list is created by putting \test
# commands in the documentation.
GENERATE_TESTLIST = YES
# The GENERATE_BUGLIST tag can be used to enable (YES) or
# disable (NO) the bug list. This list is created by putting \bug
# commands in the documentation.
GENERATE_BUGLIST = @MITK_DOXYGEN_GENERATE_BUGLIST@
# The GENERATE_DEPRECATEDLIST tag can be used to enable (YES) or
# disable (NO) the deprecated list. This list is created by putting
# \deprecated commands in the documentation.
GENERATE_DEPRECATEDLIST= @MITK_DOXYGEN_GENERATE_DEPRECATEDLIST@
# The ENABLED_SECTIONS tag can be used to enable conditional
# documentation sections, marked by \if sectionname ... \endif.
ENABLED_SECTIONS = @MITK_DOXYGEN_ENABLED_SECTIONS@
# The MAX_INITIALIZER_LINES tag determines the maximum number of lines
# the initial value of a variable or macro consists of for it to appear in
# the documentation. If the initializer consists of more lines than specified
# here it will be hidden. Use a value of 0 to hide initializers completely.
# The appearance of the initializer of individual variables and macros in the
# documentation can be controlled using \showinitializer or \hideinitializer
# command in the documentation regardless of this setting.
MAX_INITIALIZER_LINES = 0
# Set the SHOW_USED_FILES tag to NO to disable the list of files generated
# at the bottom of the documentation of classes and structs. If set to YES the
# list will mention the files that were used to generate the documentation.
SHOW_USED_FILES = YES
# If the sources in your project are distributed over multiple directories
# then setting the SHOW_DIRECTORIES tag to YES will show the directory hierarchy
# in the documentation. The default is NO.
SHOW_DIRECTORIES = NO
# Set the SHOW_FILES tag to NO to disable the generation of the Files page.
# This will remove the Files entry from the Quick Index and from the
# Folder Tree View (if specified). The default is YES.
SHOW_FILES = YES
# Set the SHOW_NAMESPACES tag to NO to disable the generation of the
# Namespaces page.
# This will remove the Namespaces entry from the Quick Index
# and from the Folder Tree View (if specified). The default is YES.
SHOW_NAMESPACES = YES
# The FILE_VERSION_FILTER tag can be used to specify a program or script that
# doxygen should invoke to get the current version for each file (typically from
# the version control system). Doxygen will invoke the program by executing (via
# popen()) the command , where is the value of
# the FILE_VERSION_FILTER tag, and is the name of an input file
# provided by doxygen. Whatever the program writes to standard output
# is used as the file version. See the manual for examples.
FILE_VERSION_FILTER =
# The LAYOUT_FILE tag can be used to specify a layout file which will be parsed
# by doxygen. The layout file controls the global structure of the generated
# output files in an output format independent way. The create the layout file
# that represents doxygen's defaults, run doxygen with the -l option.
# You can optionally specify a file name after the option, if omitted
# DoxygenLayout.xml will be used as the name of the layout file.
LAYOUT_FILE = @MITK_SOURCE_DIR@/Documentation/MITKDoxygenLayout.xml
# The CITE_BIB_FILES tag can be used to specify one or more bib files
# containing the references data. This must be a list of .bib files. The
# .bib extension is automatically appended if omitted. Using this command
# requires the bibtex tool to be installed. See also
# http://en.wikipedia.org/wiki/BibTeX for more info. For LaTeX the style
# of the bibliography can be controlled using LATEX_BIB_STYLE. To use this
# feature you need bibtex and perl available in the search path.
CITE_BIB_FILES =
#---------------------------------------------------------------------------
# configuration options related to warning and progress messages
#---------------------------------------------------------------------------
# The QUIET tag can be used to turn on/off the messages that are generated
# by doxygen. Possible values are YES and NO. If left blank NO is used.
QUIET = NO
# The WARNINGS tag can be used to turn on/off the warning messages that are
# generated by doxygen. Possible values are YES and NO. If left blank
# NO is used.
WARNINGS = YES
# If WARN_IF_UNDOCUMENTED is set to YES, then doxygen will generate warnings
# for undocumented members. If EXTRACT_ALL is set to YES then this flag will
# automatically be disabled.
WARN_IF_UNDOCUMENTED = YES
# If WARN_IF_DOC_ERROR is set to YES, doxygen will generate warnings for
# potential errors in the documentation, such as not documenting some
# parameters in a documented function, or documenting parameters that
# don't exist or using markup commands wrongly.
WARN_IF_DOC_ERROR = YES
# The WARN_NO_PARAMDOC option can be enabled to get warnings for
# functions that are documented, but have no documentation for their parameters
# or return value. If set to NO (the default) doxygen will only warn about
# wrong or incomplete parameter documentation, but not about the absence of
# documentation.
WARN_NO_PARAMDOC = NO
# The WARN_FORMAT tag determines the format of the warning messages that
# doxygen can produce. The string should contain the $file, $line, and $text
# tags, which will be replaced by the file and line number from which the
# warning originated and the warning text. Optionally the format may contain
# $version, which will be replaced by the version of the file (if it could
# be obtained via FILE_VERSION_FILTER)
WARN_FORMAT = "$file:$line: $text"
# The WARN_LOGFILE tag can be used to specify a file to which warning
# and error messages should be written. If left blank the output is written
# to stderr.
WARN_LOGFILE =
#---------------------------------------------------------------------------
# configuration options related to the input files
#---------------------------------------------------------------------------
# The INPUT tag can be used to specify the files and/or directories that contain
# documented source files. You may enter file names like "myfile.cpp" or
# directories like "/usr/src/myproject". Separate the files or directories
# with spaces.
INPUT = @MITK_SOURCE_DIR@ \
@MITK_SOURCE_DIR@/README.md \
@MITK_BINARY_DIR@ \
@MITK_DOXYGEN_ADDITIONAL_INPUT_DIRS@
# This tag can be used to specify the character encoding of the source files
# that doxygen parses. Internally doxygen uses the UTF-8 encoding, which is
# also the default input encoding. Doxygen uses libiconv (or the iconv built
# into libc) for the transcoding. See http://www.gnu.org/software/libiconv for
# the list of possible encodings.
INPUT_ENCODING = UTF-8
# If the value of the INPUT tag contains directories, you can use the
# FILE_PATTERNS tag to specify one or more wildcard pattern (like *.cpp
# and *.h) to filter out the source-files in the directories. If left
# blank the following patterns are tested:
# *.c *.cc *.cxx *.cpp *.c++ *.d *.java *.ii *.ixx *.ipp *.i++ *.inl *.h *.hh
# *.hxx *.hpp *.h++ *.idl *.odl *.cs *.php *.php3 *.inc *.m *.mm *.dox *.py
# *.f90 *.f *.for *.vhd *.vhdl
FILE_PATTERNS = *.h \
*.cpp \
*.dox \
*.md \
*.txx \
*.tpp \
*.cxx \
*.cmake
# The RECURSIVE tag can be used to turn specify whether or not subdirectories
# should be searched for input files as well. Possible values are YES and NO.
# If left blank NO is used.
RECURSIVE = YES
# The EXCLUDE tag can be used to specify files and/or directories that should be
# excluded from the INPUT source files. This way you can easily exclude a
# subdirectory from a directory tree whose root is specified with the INPUT tag.
# Note that relative paths are relative to the directory from which doxygen is
# run.
EXCLUDE = @MITK_SOURCE_DIR@/BlueBerry/Documentation/reference/api/MainPage.dox \
@MITK_SOURCE_DIR@/Utilities/IpFunc/ \
@MITK_SOURCE_DIR@/Utilities/IpSegmentation/ \
@MITK_SOURCE_DIR@/Utilities/KWStyle/ \
@MITK_SOURCE_DIR@/Utilities/Poco/ \
@MITK_SOURCE_DIR@/Utilities/qtsingleapplication/ \
@MITK_SOURCE_DIR@/Applications/PluginGenerator/ \
@MITK_SOURCE_DIR@/Core/CppMicroServices/core/doc/snippets/ \
@MITK_SOURCE_DIR@/Core/CppMicroServices/core/doc/doxygen/standalone/ \
@MITK_SOURCE_DIR@/Core/CppMicroServices/core/test/ \
@MITK_SOURCE_DIR@/Core/CppMicroServices/core/examples/ \
@MITK_SOURCE_DIR@/Core/CppMicroServices/core/src/util/jsoncpp.cpp \
@MITK_SOURCE_DIR@/Deprecated/ \
@MITK_SOURCE_DIR@/Build/ \
@MITK_SOURCE_DIR@/CMake/PackageDepends \
@MITK_SOURCE_DIR@/CMake/QBundleTemplate \
@MITK_SOURCE_DIR@/CMakeExternals \
@MITK_SOURCE_DIR@/Modules/QmitkExt/vtkQtChartHeaders/ \
@MITK_BINARY_DIR@/bin/ \
@MITK_BINARY_DIR@/PT/ \
@MITK_BINARY_DIR@/GP/ \
@MITK_BINARY_DIR@/Core/CppMicroServices/ \
@MITK_BINARY_DIR@/_CPack_Packages/ \
@MITK_DOXYGEN_ADDITIONAL_EXCLUDE_DIRS@
# The EXCLUDE_SYMLINKS tag can be used to select whether or not files or
# directories that are symbolic links (a Unix file system feature) are excluded
# from the input.
EXCLUDE_SYMLINKS = NO
# If the value of the INPUT tag contains directories, you can use the
# EXCLUDE_PATTERNS tag to specify one or more wildcard patterns to exclude
# certain files from those directories. Note that the wildcards are matched
# against the file with absolute path, so to exclude all test directories
# for example use the pattern */test/*
EXCLUDE_PATTERNS = README* \
moc_* \
ui_* \
qrc_* \
wrap_* \
Register* \
*/files.cmake \
*/.git/* \
*_p.h \
*Private.* \
*/Snippets/* \
*/snippets/* \
*/testing/* \
*/Testing/* \
@MITK_BINARY_DIR@/*.cmake \
@MITK_DOXYGEN_EXCLUDE_PATTERNS@
# The EXCLUDE_SYMBOLS tag can be used to specify one or more symbol names
# (namespaces, classes, functions, etc.) that should be excluded from the
# output. The symbol name can be a fully qualified name, a word, or if the
# wildcard * is used, a substring. Examples: ANamespace, AClass,
# AClass::ANamespace, ANamespace::*Test
EXCLUDE_SYMBOLS =
# The EXAMPLE_PATH tag can be used to specify one or more files or
# directories that contain example code fragments that are included (see
# the \include command).
EXAMPLE_PATH = @MITK_SOURCE_DIR@/Examples/ \
@MITK_SOURCE_DIR@/Examples/Tutorial/ \
@MITK_SOURCE_DIR@/Examples/Plugins/ \
@MITK_SOURCE_DIR@/Examples/QtFreeRender/ \
@MITK_SOURCE_DIR@/Core/Code/ \
@MITK_SOURCE_DIR@/Core/CppMicroServices/core/doc/snippets/ \
@MITK_SOURCE_DIR@/Core/CppMicroServices/core/examples/ \
@MITK_DOXYGEN_OUTPUT_DIR@/html/extension-points/html/ \
@MITK_SOURCE_DIR@/Documentation/Snippets/ \
@MITK_SOURCE_DIR@/Documentation/Doxygen/ExampleCode/ \
@MITK_SOURCE_DIR@/Modules/OpenCL/Documentation/doxygen/snippets/ \
@MITK_SOURCE_DIR@/Modules/IGT/Tutorial/
# If the value of the EXAMPLE_PATH tag contains directories, you can use the
# EXAMPLE_PATTERNS tag to specify one or more wildcard pattern (like *.cpp
# and *.h) to filter out the source-files in the directories. If left
# blank all files are included.
EXAMPLE_PATTERNS =
# If the EXAMPLE_RECURSIVE tag is set to YES then subdirectories will be
# searched for input files to be used with the \include or \dontinclude
# commands irrespective of the value of the RECURSIVE tag.
# Possible values are YES and NO. If left blank NO is used.
EXAMPLE_RECURSIVE = YES
# The IMAGE_PATH tag can be used to specify one or more files or
# directories that contain image that are included in the documentation (see
# the \image command).
IMAGE_PATH = @MITK_SOURCE_DIR@/Documentation/Doxygen/ \
@MITK_SOURCE_DIR@/Documentation/Doxygen/Modules/ \
@MITK_SOURCE_DIR@/Documentation/Doxygen/Tutorial/ \
@MITK_SOURCE_DIR@
# The INPUT_FILTER tag can be used to specify a program that doxygen should
# invoke to filter for each input file. Doxygen will invoke the filter program
# by executing (via popen()) the command , where
# is the value of the INPUT_FILTER tag, and is the name of an
# input file. Doxygen will then use the output that the filter program writes
# to standard output.
# If FILTER_PATTERNS is specified, this tag will be
# ignored.
INPUT_FILTER =
# The FILTER_PATTERNS tag can be used to specify filters on a per file pattern
# basis.
# Doxygen will compare the file name with each pattern and apply the
# filter if there is a match.
# The filters are a list of the form:
# pattern=filter (like *.cpp=my_cpp_filter). See INPUT_FILTER for further
# info on how filters are used. If FILTER_PATTERNS is empty or if
# non of the patterns match the file name, INPUT_FILTER is applied.
FILTER_PATTERNS = *.cmake=@CMakeDoxygenFilter_EXECUTABLE@
# If the FILTER_SOURCE_FILES tag is set to YES, the input filter (if set using
# INPUT_FILTER) will be used to filter the input files when producing source
# files to browse (i.e. when SOURCE_BROWSER is set to YES).
FILTER_SOURCE_FILES = NO
# The FILTER_SOURCE_PATTERNS tag can be used to specify source filters per file
# pattern. A pattern will override the setting for FILTER_PATTERN (if any)
# and it is also possible to disable source filtering for a specific pattern
# using *.ext= (so without naming a filter). This option only has effect when
# FILTER_SOURCE_FILES is enabled.
FILTER_SOURCE_PATTERNS =
#---------------------------------------------------------------------------
# configuration options related to source browsing
#---------------------------------------------------------------------------
# If the SOURCE_BROWSER tag is set to YES then a list of source files will
# be generated. Documented entities will be cross-referenced with these sources.
# Note: To get rid of all source code in the generated output, make sure also
# VERBATIM_HEADERS is set to NO.
SOURCE_BROWSER = YES
# Setting the INLINE_SOURCES tag to YES will include the body
# of functions and classes directly in the documentation.
INLINE_SOURCES = NO
# Setting the STRIP_CODE_COMMENTS tag to YES (the default) will instruct
# doxygen to hide any special comment blocks from generated source code
# fragments. Normal C and C++ comments will always remain visible.
STRIP_CODE_COMMENTS = YES
# If the REFERENCED_BY_RELATION tag is set to YES
# then for each documented function all documented
# functions referencing it will be listed.
REFERENCED_BY_RELATION = YES
# If the REFERENCES_RELATION tag is set to YES
# then for each documented function all documented entities
# called/used by that function will be listed.
REFERENCES_RELATION = YES
# If the REFERENCES_LINK_SOURCE tag is set to YES (the default)
# and SOURCE_BROWSER tag is set to YES, then the hyperlinks from
# functions in REFERENCES_RELATION and REFERENCED_BY_RELATION lists will
# link to the source code.
# Otherwise they will link to the documentation.
REFERENCES_LINK_SOURCE = YES
# If the USE_HTAGS tag is set to YES then the references to source code
# will point to the HTML generated by the htags(1) tool instead of doxygen
# built-in source browser. The htags tool is part of GNU's global source
# tagging system (see http://www.gnu.org/software/global/global.html). You
# will need version 4.8.6 or higher.
USE_HTAGS = NO
# If the VERBATIM_HEADERS tag is set to YES (the default) then Doxygen
# will generate a verbatim copy of the header file for each class for
# which an include is specified. Set to NO to disable this.
VERBATIM_HEADERS = YES
#---------------------------------------------------------------------------
# configuration options related to the alphabetical class index
#---------------------------------------------------------------------------
# If the ALPHABETICAL_INDEX tag is set to YES, an alphabetical index
# of all compounds will be generated. Enable this if the project
# contains a lot of classes, structs, unions or interfaces.
ALPHABETICAL_INDEX = YES
# If the alphabetical index is enabled (see ALPHABETICAL_INDEX) then
# the COLS_IN_ALPHA_INDEX tag can be used to specify the number of columns
# in which this list will be split (can be a number in the range [1..20])
COLS_IN_ALPHA_INDEX = 3
# In case all classes in a project start with a common prefix, all
# classes will be put under the same header in the alphabetical index.
# The IGNORE_PREFIX tag can be used to specify one or more prefixes that
# should be ignored while generating the index headers.
IGNORE_PREFIX =
#---------------------------------------------------------------------------
# configuration options related to the HTML output
#---------------------------------------------------------------------------
# If the GENERATE_HTML tag is set to YES (the default) Doxygen will
# generate HTML output.
GENERATE_HTML = YES
# The HTML_OUTPUT tag is used to specify where the HTML docs will be put.
# If a relative path is entered the value of OUTPUT_DIRECTORY will be
# put in front of it. If left blank `html' will be used as the default path.
HTML_OUTPUT = html
# The HTML_FILE_EXTENSION tag can be used to specify the file extension for
# each generated HTML page (for example: .htm,.php,.asp). If it is left blank
# doxygen will generate files with .html extension.
HTML_FILE_EXTENSION = .html
# The HTML_HEADER tag can be used to specify a personal HTML header for
# each generated HTML page. If it is left blank doxygen will generate a
# standard header. Note that when using a custom header you are responsible
# for the proper inclusion of any scripts and style sheets that doxygen
# needs, which is dependent on the configuration options used.
# It is advised to generate a default header using "doxygen -w html
# header.html footer.html stylesheet.css YourConfigFile" and then modify
# that header. Note that the header is subject to change so you typically
# have to redo this when upgrading to a newer version of doxygen or when
# changing the value of configuration settings such as GENERATE_TREEVIEW!
HTML_HEADER =
# The HTML_FOOTER tag can be used to specify a personal HTML footer for
# each generated HTML page. If it is left blank doxygen will generate a
# standard footer.
HTML_FOOTER =
# The HTML_STYLESHEET tag can be used to specify a user-defined cascading
# style sheet that is used by each HTML page. It can be used to
# fine-tune the look of the HTML output. If the tag is left blank doxygen
# will generate a default style sheet. Note that doxygen will try to copy
# the style sheet file to the HTML output directory, so don't put your own
# style sheet in the HTML output directory as well, or it will be erased!
HTML_STYLESHEET = @MITK_DOXYGEN_STYLESHEET@
# The HTML_EXTRA_FILES tag can be used to specify one or more extra images or
# other source files which should be copied to the HTML output directory. Note
# that these files will be copied to the base HTML output directory. Use the
# $relpath$ marker in the HTML_HEADER and/or HTML_FOOTER files to load these
# files. In the HTML_STYLESHEET file, use the file name only. Also note that
# the files will be copied as-is; there are no commands or markers available.
HTML_EXTRA_FILES =
# The HTML_COLORSTYLE_HUE tag controls the color of the HTML output.
# Doxygen will adjust the colors in the style sheet and background images
# according to this color. Hue is specified as an angle on a colorwheel,
# see http://en.wikipedia.org/wiki/Hue for more information.
# For instance the value 0 represents red, 60 is yellow, 120 is green,
# 180 is cyan, 240 is blue, 300 purple, and 360 is red again.
# The allowed range is 0 to 359.
HTML_COLORSTYLE_HUE = 220
# The HTML_COLORSTYLE_SAT tag controls the purity (or saturation) of
# the colors in the HTML output. For a value of 0 the output will use
# grayscales only. A value of 255 will produce the most vivid colors.
HTML_COLORSTYLE_SAT = 100
# The HTML_COLORSTYLE_GAMMA tag controls the gamma correction applied to
# the luminance component of the colors in the HTML output. Values below
# 100 gradually make the output lighter, whereas values above 100 make
# the output darker. The value divided by 100 is the actual gamma applied,
# so 80 represents a gamma of 0.8, The value 220 represents a gamma of 2.2,
# and 100 does not change the gamma.
HTML_COLORSTYLE_GAMMA = 80
# If the HTML_TIMESTAMP tag is set to YES then the footer of each generated HTML
# page will contain the date and time when the page was generated. Setting
# this to NO can help when comparing the output of multiple runs.
HTML_TIMESTAMP = YES
# If the HTML_ALIGN_MEMBERS tag is set to YES, the members of classes,
# files or namespaces will be aligned in HTML using tables. If set to
# NO a bullet list will be used.
HTML_ALIGN_MEMBERS = YES
# If the HTML_DYNAMIC_SECTIONS tag is set to YES then the generated HTML
# documentation will contain sections that can be hidden and shown after the
# page has loaded. For this to work a browser that supports
# JavaScript and DHTML is required (for instance Mozilla 1.0+, Firefox
# Netscape 6.0+, Internet explorer 5.0+, Konqueror, or Safari).
HTML_DYNAMIC_SECTIONS = @MITK_DOXYGEN_HTML_DYNAMIC_SECTIONS@
# If the GENERATE_DOCSET tag is set to YES, additional index files
# will be generated that can be used as input for Apple's Xcode 3
# integrated development environment, introduced with OSX 10.5 (Leopard).
# To create a documentation set, doxygen will generate a Makefile in the
# HTML output directory. Running make will produce the docset in that
# directory and running "make install" will install the docset in
# ~/Library/Developer/Shared/Documentation/DocSets so that Xcode will find
# it at startup.
# See http://developer.apple.com/tools/creatingdocsetswithdoxygen.html
# for more information.
GENERATE_DOCSET = NO
# When GENERATE_DOCSET tag is set to YES, this tag determines the name of the
# feed. A documentation feed provides an umbrella under which multiple
# documentation sets from a single provider (such as a company or product suite)
# can be grouped.
DOCSET_FEEDNAME = "Doxygen generated docs"
# When GENERATE_DOCSET tag is set to YES, this tag specifies a string that
# should uniquely identify the documentation set bundle. This should be a
# reverse domain-name style string, e.g. com.mycompany.MyDocSet. Doxygen
# will append .docset to the name.
DOCSET_BUNDLE_ID = org.doxygen.Project
# When GENERATE_PUBLISHER_ID tag specifies a string that should uniquely identify
# the documentation publisher. This should be a reverse domain-name style
# string, e.g. com.mycompany.MyDocSet.documentation.
DOCSET_PUBLISHER_ID = org.doxygen.Publisher
# The GENERATE_PUBLISHER_NAME tag identifies the documentation publisher.
DOCSET_PUBLISHER_NAME = Publisher
# If the GENERATE_HTMLHELP tag is set to YES, additional index files
# will be generated that can be used as input for tools like the
# Microsoft HTML help workshop to generate a compiled HTML help file (.chm)
# of the generated HTML documentation.
GENERATE_HTMLHELP = NO
# If the GENERATE_HTMLHELP tag is set to YES, the CHM_FILE tag can
# be used to specify the file name of the resulting .chm file. You
# can add a path in front of the file if the result should not be
# written to the html output directory.
CHM_FILE =
# If the GENERATE_HTMLHELP tag is set to YES, the HHC_LOCATION tag can
# be used to specify the location (absolute path including file name) of
# the HTML help compiler (hhc.exe). If non-empty doxygen will try to run
# the HTML help compiler on the generated index.hhp.
HHC_LOCATION =
# If the GENERATE_HTMLHELP tag is set to YES, the GENERATE_CHI flag
# controls if a separate .chi index file is generated (YES) or that
# it should be included in the master .chm file (NO).
GENERATE_CHI = NO
# If the GENERATE_HTMLHELP tag is set to YES, the CHM_INDEX_ENCODING
# is used to encode HtmlHelp index (hhk), content (hhc) and project file
# content.
CHM_INDEX_ENCODING =
# If the GENERATE_HTMLHELP tag is set to YES, the BINARY_TOC flag
# controls whether a binary table of contents is generated (YES) or a
# normal table of contents (NO) in the .chm file.
BINARY_TOC = NO
# The TOC_EXPAND flag can be set to YES to add extra items for group members
# to the contents of the HTML help documentation and to the tree view.
TOC_EXPAND = NO
# If the GENERATE_QHP tag is set to YES and both QHP_NAMESPACE and
# QHP_VIRTUAL_FOLDER are set, an additional index file will be generated
# that can be used as input for Qt's qhelpgenerator to generate a
# Qt Compressed Help (.qch) of the generated HTML documentation.
GENERATE_QHP = @MITK_DOXYGEN_GENERATE_QHP@
# If the QHG_LOCATION tag is specified, the QCH_FILE tag can
# be used to specify the file name of the resulting .qch file.
# The path specified is relative to the HTML output folder.
QCH_FILE = @MITK_DOXYGEN_QCH_FILE@
# The QHP_NAMESPACE tag specifies the namespace to use when generating
# Qt Help Project output. For more information please see
# http://doc.trolltech.com/qthelpproject.html#namespace
QHP_NAMESPACE = "org.mitk"
# The QHP_VIRTUAL_FOLDER tag specifies the namespace to use when generating
# Qt Help Project output. For more information please see
# http://doc.trolltech.com/qthelpproject.html#virtual-folders
QHP_VIRTUAL_FOLDER = MITK
# If QHP_CUST_FILTER_NAME is set, it specifies the name of a custom filter to
# add. For more information please see
# http://doc.trolltech.com/qthelpproject.html#custom-filters
QHP_CUST_FILTER_NAME =
# The QHP_CUST_FILT_ATTRS tag specifies the list of the attributes of the
# custom filter to add. For more information please see
#
# Qt Help Project / Custom Filters.
QHP_CUST_FILTER_ATTRS =
# The QHP_SECT_FILTER_ATTRS tag specifies the list of the attributes this
# project's
# filter section matches.
#
# Qt Help Project / Filter Attributes.
QHP_SECT_FILTER_ATTRS =
# If the GENERATE_QHP tag is set to YES, the QHG_LOCATION tag can
# be used to specify the location of Qt's qhelpgenerator.
# If non-empty doxygen will try to run qhelpgenerator on the generated
# .qhp file.
QHG_LOCATION = @QT_HELPGENERATOR_EXECUTABLE@
# If the GENERATE_ECLIPSEHELP tag is set to YES, additional index files
# will be generated, which together with the HTML files, form an Eclipse help
# plugin. To install this plugin and make it available under the help contents
# menu in Eclipse, the contents of the directory containing the HTML and XML
# files needs to be copied into the plugins directory of eclipse. The name of
# the directory within the plugins directory should be the same as
# the ECLIPSE_DOC_ID value. After copying Eclipse needs to be restarted before
# the help appears.
GENERATE_ECLIPSEHELP = NO
# A unique identifier for the eclipse help plugin. When installing the plugin
# the directory name containing the HTML and XML files should also have
# this name.
ECLIPSE_DOC_ID = org.doxygen.Project
# The DISABLE_INDEX tag can be used to turn on/off the condensed index (tabs)
# at top of each HTML page. The value NO (the default) enables the index and
# the value YES disables it. Since the tabs have the same information as the
# navigation tree you can set this option to NO if you already set
# GENERATE_TREEVIEW to YES.
DISABLE_INDEX = NO
# The GENERATE_TREEVIEW tag is used to specify whether a tree-like index
# structure should be generated to display hierarchical information.
# If the tag value is set to YES, a side panel will be generated
# containing a tree-like index structure (just like the one that
# is generated for HTML Help). For this to work a browser that supports
# JavaScript, DHTML, CSS and frames is required (i.e. any modern browser).
# Windows users are probably better off using the HTML help feature.
# Since the tree basically has the same information as the tab index you
# could consider to set DISABLE_INDEX to NO when enabling this option.
GENERATE_TREEVIEW = YES
# The ENUM_VALUES_PER_LINE tag can be used to set the number of enum values
# (range [0,1..20]) that doxygen will group on one line in the generated HTML
# documentation. Note that a value of 0 will completely suppress the enum
# values from appearing in the overview section.
ENUM_VALUES_PER_LINE = 4
# By enabling USE_INLINE_TREES, doxygen will generate the Groups, Directories,
# and Class Hierarchy pages using a tree view instead of an ordered list.
USE_INLINE_TREES = NO
# If the treeview is enabled (see GENERATE_TREEVIEW) then this tag can be
# used to set the initial width (in pixels) of the frame in which the tree
# is shown.
TREEVIEW_WIDTH = 300
# When the EXT_LINKS_IN_WINDOW option is set to YES doxygen will open
# links to external symbols imported via tag files in a separate window.
EXT_LINKS_IN_WINDOW = NO
# Use this tag to change the font size of Latex formulas included
# as images in the HTML documentation. The default is 10. Note that
# when you change the font size after a successful doxygen run you need
# to manually remove any form_*.png images from the HTML output directory
# to force them to be regenerated.
FORMULA_FONTSIZE = 10
# Use the FORMULA_TRANPARENT tag to determine whether or not the images
# generated for formulas are transparent PNGs. Transparent PNGs are
# not supported properly for IE 6.0, but are supported on all modern browsers.
# Note that when changing this option you need to delete any form_*.png files
# in the HTML output before the changes have effect.
FORMULA_TRANSPARENT = YES
# Enable the USE_MATHJAX option to render LaTeX formulas using MathJax
# (see http://www.mathjax.org) which uses client side Javascript for the
# rendering instead of using prerendered bitmaps. Use this if you do not
# have LaTeX installed or if you want to formulas look prettier in the HTML
# output. When enabled you may also need to install MathJax separately and
# configure the path to it using the MATHJAX_RELPATH option.
-USE_MATHJAX = NO
+USE_MATHJAX = YES
# When MathJax is enabled you need to specify the location relative to the
# HTML output directory using the MATHJAX_RELPATH option. The destination
# directory should contain the MathJax.js script. For instance, if the mathjax
# directory is located at the same level as the HTML output directory, then
# MATHJAX_RELPATH should be ../mathjax. The default value points to
# the MathJax Content Delivery Network so you can quickly see the result without
# installing MathJax.
# However, it is strongly recommended to install a local
# copy of MathJax from http://www.mathjax.org before deployment.
MATHJAX_RELPATH = http://www.mathjax.org/mathjax
# The MATHJAX_EXTENSIONS tag can be used to specify one or MathJax extension
# names that should be enabled during MathJax rendering.
MATHJAX_EXTENSIONS =
# When the SEARCHENGINE tag is enabled doxygen will generate a search box
# for the HTML output. The underlying search engine uses javascript
# and DHTML and should work on any modern browser. Note that when using
# HTML help (GENERATE_HTMLHELP), Qt help (GENERATE_QHP), or docsets
# (GENERATE_DOCSET) there is already a search function so this one should
# typically be disabled. For large projects the javascript based search engine
# can be slow, then enabling SERVER_BASED_SEARCH may provide a better solution.
SEARCHENGINE = YES
# When the SERVER_BASED_SEARCH tag is enabled the search engine will be
# implemented using a PHP enabled web server instead of at the web client
# using Javascript. Doxygen will generate the search PHP script and index
# file to put on the web server. The advantage of the server
# based approach is that it scales better to large projects and allows
# full text search. The disadvantages are that it is more difficult to setup
# and does not have live searching capabilities.
SERVER_BASED_SEARCH = NO
#---------------------------------------------------------------------------
# configuration options related to the LaTeX output
#---------------------------------------------------------------------------
# If the GENERATE_LATEX tag is set to YES (the default) Doxygen will
# generate Latex output.
GENERATE_LATEX = NO
# The LATEX_OUTPUT tag is used to specify where the LaTeX docs will be put.
# If a relative path is entered the value of OUTPUT_DIRECTORY will be
# put in front of it. If left blank `latex' will be used as the default path.
LATEX_OUTPUT = latex
# The LATEX_CMD_NAME tag can be used to specify the LaTeX command name to be
# invoked. If left blank `latex' will be used as the default command name.
# Note that when enabling USE_PDFLATEX this option is only used for
# generating bitmaps for formulas in the HTML output, but not in the
# Makefile that is written to the output directory.
LATEX_CMD_NAME = latex
# The MAKEINDEX_CMD_NAME tag can be used to specify the command name to
# generate index for LaTeX. If left blank `makeindex' will be used as the
# default command name.
MAKEINDEX_CMD_NAME = makeindex
# If the COMPACT_LATEX tag is set to YES Doxygen generates more compact
# LaTeX documents. This may be useful for small projects and may help to
# save some trees in general.
COMPACT_LATEX = NO
# The PAPER_TYPE tag can be used to set the paper type that is used
# by the printer. Possible values are: a4, letter, legal and
# executive. If left blank a4wide will be used.
PAPER_TYPE = a4wide
# The EXTRA_PACKAGES tag can be to specify one or more names of LaTeX
# packages that should be included in the LaTeX output.
EXTRA_PACKAGES = amssymb
# The LATEX_HEADER tag can be used to specify a personal LaTeX header for
# the generated latex document. The header should contain everything until
# the first chapter. If it is left blank doxygen will generate a
# standard header. Notice: only use this tag if you know what you are doing!
LATEX_HEADER =
# The LATEX_FOOTER tag can be used to specify a personal LaTeX footer for
# the generated latex document. The footer should contain everything after
# the last chapter. If it is left blank doxygen will generate a
# standard footer. Notice: only use this tag if you know what you are doing!
LATEX_FOOTER =
# If the PDF_HYPERLINKS tag is set to YES, the LaTeX that is generated
# is prepared for conversion to pdf (using ps2pdf). The pdf file will
# contain links (just like the HTML output) instead of page references
# This makes the output suitable for online browsing using a pdf viewer.
PDF_HYPERLINKS = NO
# If the USE_PDFLATEX tag is set to YES, pdflatex will be used instead of
# plain latex in the generated Makefile. Set this option to YES to get a
# higher quality PDF documentation.
USE_PDFLATEX = NO
# If the LATEX_BATCHMODE tag is set to YES, doxygen will add the \\batchmode.
# command to the generated LaTeX files. This will instruct LaTeX to keep
# running if errors occur, instead of asking the user for help.
# This option is also used when generating formulas in HTML.
LATEX_BATCHMODE = NO
# If LATEX_HIDE_INDICES is set to YES then doxygen will not
# include the index chapters (such as File Index, Compound Index, etc.)
# in the output.
LATEX_HIDE_INDICES = NO
# If LATEX_SOURCE_CODE is set to YES then doxygen will include
# source code with syntax highlighting in the LaTeX output.
# Note that which sources are shown also depends on other settings
# such as SOURCE_BROWSER.
LATEX_SOURCE_CODE = NO
# The LATEX_BIB_STYLE tag can be used to specify the style to use for the
# bibliography, e.g. plainnat, or ieeetr. The default style is "plain". See
# http://en.wikipedia.org/wiki/BibTeX for more info.
LATEX_BIB_STYLE = plain
#---------------------------------------------------------------------------
# configuration options related to the RTF output
#---------------------------------------------------------------------------
# If the GENERATE_RTF tag is set to YES Doxygen will generate RTF output
# The RTF output is optimized for Word 97 and may not look very pretty with
# other RTF readers or editors.
GENERATE_RTF = NO
# The RTF_OUTPUT tag is used to specify where the RTF docs will be put.
# If a relative path is entered the value of OUTPUT_DIRECTORY will be
# put in front of it. If left blank `rtf' will be used as the default path.
RTF_OUTPUT = rtf
# If the COMPACT_RTF tag is set to YES Doxygen generates more compact
# RTF documents. This may be useful for small projects and may help to
# save some trees in general.
COMPACT_RTF = NO
# If the RTF_HYPERLINKS tag is set to YES, the RTF that is generated
# will contain hyperlink fields. The RTF file will
# contain links (just like the HTML output) instead of page references.
# This makes the output suitable for online browsing using WORD or other
# programs which support those fields.
# Note: wordpad (write) and others do not support links.
RTF_HYPERLINKS = NO
# Load style sheet definitions from file. Syntax is similar to doxygen's
# config file, i.e. a series of assignments. You only have to provide
# replacements, missing definitions are set to their default value.
RTF_STYLESHEET_FILE =
# Set optional variables used in the generation of an rtf document.
# Syntax is similar to doxygen's config file.
RTF_EXTENSIONS_FILE =
#---------------------------------------------------------------------------
# configuration options related to the man page output
#---------------------------------------------------------------------------
# If the GENERATE_MAN tag is set to YES (the default) Doxygen will
# generate man pages
GENERATE_MAN = NO
# The MAN_OUTPUT tag is used to specify where the man pages will be put.
# If a relative path is entered the value of OUTPUT_DIRECTORY will be
# put in front of it. If left blank `man' will be used as the default path.
MAN_OUTPUT = man
# The MAN_EXTENSION tag determines the extension that is added to
# the generated man pages (default is the subroutine's section .3)
MAN_EXTENSION = .3
# If the MAN_LINKS tag is set to YES and Doxygen generates man output,
# then it will generate one additional man file for each entity
# documented in the real man page(s). These additional files
# only source the real man page, but without them the man command
# would be unable to find the correct page. The default is NO.
MAN_LINKS = NO
#---------------------------------------------------------------------------
# configuration options related to the XML output
#---------------------------------------------------------------------------
# If the GENERATE_XML tag is set to YES Doxygen will
# generate an XML file that captures the structure of
# the code including all documentation.
GENERATE_XML = NO
# The XML_OUTPUT tag is used to specify where the XML pages will be put.
# If a relative path is entered the value of OUTPUT_DIRECTORY will be
# put in front of it. If left blank `xml' will be used as the default path.
XML_OUTPUT = xml
# The XML_SCHEMA tag can be used to specify an XML schema,
# which can be used by a validating XML parser to check the
# syntax of the XML files.
XML_SCHEMA =
# The XML_DTD tag can be used to specify an XML DTD,
# which can be used by a validating XML parser to check the
# syntax of the XML files.
XML_DTD =
# If the XML_PROGRAMLISTING tag is set to YES Doxygen will
# dump the program listings (including syntax highlighting
# and cross-referencing information) to the XML output. Note that
# enabling this will significantly increase the size of the XML output.
XML_PROGRAMLISTING = YES
#---------------------------------------------------------------------------
# configuration options for the AutoGen Definitions output
#---------------------------------------------------------------------------
# If the GENERATE_AUTOGEN_DEF tag is set to YES Doxygen will
# generate an AutoGen Definitions (see autogen.sf.net) file
# that captures the structure of the code including all
# documentation. Note that this feature is still experimental
# and incomplete at the moment.
GENERATE_AUTOGEN_DEF = NO
#---------------------------------------------------------------------------
# configuration options related to the Perl module output
#---------------------------------------------------------------------------
# If the GENERATE_PERLMOD tag is set to YES Doxygen will
# generate a Perl module file that captures the structure of
# the code including all documentation. Note that this
# feature is still experimental and incomplete at the
# moment.
GENERATE_PERLMOD = NO
# If the PERLMOD_LATEX tag is set to YES Doxygen will generate
# the necessary Makefile rules, Perl scripts and LaTeX code to be able
# to generate PDF and DVI output from the Perl module output.
PERLMOD_LATEX = NO
# If the PERLMOD_PRETTY tag is set to YES the Perl module output will be
# nicely formatted so it can be parsed by a human reader.
# This is useful
# if you want to understand what is going on.
# On the other hand, if this
# tag is set to NO the size of the Perl module output will be much smaller
# and Perl will parse it just the same.
PERLMOD_PRETTY = YES
# The names of the make variables in the generated doxyrules.make file
# are prefixed with the string contained in PERLMOD_MAKEVAR_PREFIX.
# This is useful so different doxyrules.make files included by the same
# Makefile don't overwrite each other's variables.
PERLMOD_MAKEVAR_PREFIX =
#---------------------------------------------------------------------------
# Configuration options related to the preprocessor
#---------------------------------------------------------------------------
# If the ENABLE_PREPROCESSING tag is set to YES (the default) Doxygen will
# evaluate all C-preprocessor directives found in the sources and include
# files.
ENABLE_PREPROCESSING = YES
# If the MACRO_EXPANSION tag is set to YES Doxygen will expand all macro
# names in the source code. If set to NO (the default) only conditional
# compilation will be performed. Macro expansion can be done in a controlled
# way by setting EXPAND_ONLY_PREDEF to YES.
MACRO_EXPANSION = YES
# If the EXPAND_ONLY_PREDEF and MACRO_EXPANSION tags are both set to YES
# then the macro expansion is limited to the macros specified with the
# PREDEFINED and EXPAND_AS_DEFINED tags.
EXPAND_ONLY_PREDEF = NO
# If the SEARCH_INCLUDES tag is set to YES (the default) the includes files
# pointed to by INCLUDE_PATH will be searched when a #include is found.
SEARCH_INCLUDES = YES
# The INCLUDE_PATH tag can be used to specify one or more directories that
# contain include files that are not input files but should be processed by
# the preprocessor.
INCLUDE_PATH =
# You can use the INCLUDE_FILE_PATTERNS tag to specify one or more wildcard
# patterns (like *.h and *.hpp) to filter out the header-files in the
# directories. If left blank, the patterns specified with FILE_PATTERNS will
# be used.
INCLUDE_FILE_PATTERNS =
# The PREDEFINED tag can be used to specify one or more macro names that
# are defined before the preprocessor is started (similar to the -D option of
# gcc). The argument of the tag is a list of macros of the form: name
# or name=definition (no spaces). If the definition and the = are
# omitted =1 is assumed. To prevent a macro definition from being
# undefined via #undef or recursively expanded use the := operator
# instead of the = operator.
PREDEFINED = itkNotUsed(x)= \
"itkSetMacro(name,type)= virtual void Set##name (type _arg);" \
"itkGetMacro(name,type)= virtual type Get##name ();" \
"itkGetConstMacro(name,type)= virtual type Get##name () const;" \
"itkSetStringMacro(name)= virtual void Set##name (const char* _arg);" \
"itkGetStringMacro(name)= virtual const char* Get##name () const;" \
"itkSetClampMacro(name,type,min,max)= virtual void Set##name (type _arg);" \
"itkSetObjectMacro(name,type)= virtual void Set##name (type* _arg);" \
"itkGetObjectMacro(name,type)= virtual type* Get##name ();" \
"itkSetConstObjectMacro(name,type)= virtual void Set##name ( const type* _arg);" \
"itkGetConstObjectMacro(name,type)= virtual const type* Get##name ();" \
"itkGetConstReferenceMacro(name,type)= virtual const type& Get##name ();" \
"itkGetConstReferenceObjectMacro(name,type)= virtual const type::Pointer& Get##name () const;" \
"itkBooleanMacro(name)= virtual void name##On (); virtual void name##Off ();" \
"itkSetVector2Macro(name,type)= virtual void Set##name (type _arg1, type _arg2) virtual void Set##name (type _arg[2]);" \
"itkGetVector2Macro(name,type)= virtual type* Get##name () const; virtual void Get##name (type& _arg1, type& _arg2) const; virtual void Get##name (type _arg[2]) const;" \
"itkSetVector3Macro(name,type)= virtual void Set##name (type _arg1, type _arg2, type _arg3) virtual void Set##name (type _arg[3]);" \
"itkGetVector3Macro(name,type)= virtual type* Get##name () const; virtual void Get##name (type& _arg1, type& _arg2, type& _arg3) const; virtual void Get##name (type _arg[3]) const;" \
"itkSetVector4Macro(name,type)= virtual void Set##name (type _arg1, type _arg2, type _arg3, type _arg4) virtual void Set##name (type _arg[4]);" \
"itkGetVector4Macro(name,type)= virtual type* Get##name () const; virtual void Get##name (type& _arg1, type& _arg2, type& _arg3, type& _arg4) const; virtual void Get##name (type _arg[4]) const;" \
"itkSetVector6Macro(name,type)= virtual void Set##name (type _arg1, type _arg2, type _arg3, type _arg4, type _arg5, type _arg6) virtual void Set##name (type _arg[6]);" \
"itkGetVector6Macro(name,type)= virtual type* Get##name () const; virtual void Get##name (type& _arg1, type& _arg2, type& _arg3, type& _arg4, type& _arg5, type& _arg6) const; virtual void Get##name (type _arg[6]) const;" \
"itkSetVectorMacro(name,type,count)= virtual void Set##name(type data[]);" \
"itkGetVectorMacro(name,type,count)= virtual type* Get##name () const;" \
"itkNewMacro(type)= static Pointer New();" \
"itkFactorylessNewMacro(type)= static Pointer New();" \
"itkCloneMacro(type)= Pointer Clone() const;" \
"itkTypeMacro(thisClass,superclass)= virtual const char *GetClassName() const;" \
"itkConceptMacro(name,concept)= enum { name = 0 };" \
"ITK_NUMERIC_LIMITS= std::numeric_limits" \
"ITK_TYPENAME= typename" \
"FEM_ABSTRACT_CLASS(thisClass,parentClass)= public: /** Standard Self typedef.*/ typedef thisClass Self; /** Standard Superclass typedef. */ typedef parentClass Superclass; /** Pointer or SmartPointer to an object. */ typedef Self* Pointer; /** Const pointer or SmartPointer to an object. */ typedef const Self* ConstPointer; private:" \
"FEM_CLASS(thisClass,parentClass)= FEM_ABSTRACT_CLASS(thisClass,parentClass) public: /** Create a new object from the existing one */ virtual Baseclass::Pointer Clone() const; /** Class ID for FEM object factory */ static const int CLID; /** Virtual function to access the class ID */ virtual int ClassID() const { return CLID; } /** Object creation in an itk compatible way */ static Self::Pointer New() { return new Self(); } private:" \
FREEVERSION \
ERROR_CHECKING \
HAS_TIFF \
HAS_JPEG \
HAS_NETLIB \
HAS_PNG \
HAS_ZLIB \
HAS_GLUT \
HAS_QT \
VCL_USE_NATIVE_STL=1 \
VCL_USE_NATIVE_COMPLEX=1 \
VCL_HAS_BOOL=1 \
VXL_BIG_ENDIAN=1 \
VXL_LITTLE_ENDIAN=0 \
VNL_DLL_DATA= \
size_t=vcl_size_t \
"US_PREPEND_NAMESPACE(x)=mitk::x" \
"US_BEGIN_NAMESPACE= namespace mitk {" \
"US_END_NAMESPACE=}" \
"US_BASECLASS_NAME=itk::LightObject" \
US_EXPORT= \
"DEPRECATED(func)=func"
# If the MACRO_EXPANSION and EXPAND_ONLY_PREDEF tags are set to YES then
# this tag can be used to specify a list of macro names that should be expanded.
# The macro definition that is found in the sources will be used.
# Use the PREDEFINED tag if you want to use a different macro definition that
# overrules the definition found in the source code.
EXPAND_AS_DEFINED =
# If the SKIP_FUNCTION_MACROS tag is set to YES (the default) then
# doxygen's preprocessor will remove all references to function-like macros
# that are alone on a line, have an all uppercase name, and do not end with a
# semicolon, because these will confuse the parser if not removed.
SKIP_FUNCTION_MACROS = YES
#---------------------------------------------------------------------------
# Configuration::additions related to external references
#---------------------------------------------------------------------------
# The TAGFILES option can be used to specify one or more tagfiles. For each
# tag file the location of the external documentation should be added. The
# format of a tag file without this location is as follows:
#
# TAGFILES = file1 file2 ...
# Adding location for the tag files is done as follows:
#
# TAGFILES = file1=loc1 "file2 = loc2" ...
# where "loc1" and "loc2" can be relative or absolute paths
# or URLs. Note that each tag file must have a unique name (where the name does
# NOT include the path). If a tag file is not located in the directory in which
# doxygen is run, you must also specify the path to the tagfile here.
TAGFILES = @BLUEBERRY_DOXYGEN_TAGFILE@
# When a file name is specified after GENERATE_TAGFILE, doxygen will create
# a tag file that is based on the input files it reads.
GENERATE_TAGFILE = @MITK_DOXYGEN_TAGFILE_NAME@
# If the ALLEXTERNALS tag is set to YES all external classes will be listed
# in the class index. If set to NO only the inherited external classes
# will be listed.
ALLEXTERNALS = NO
# If the EXTERNAL_GROUPS tag is set to YES all external groups will be listed
# in the modules index. If set to NO, only the current project's groups will
# be listed.
EXTERNAL_GROUPS = NO
# The PERL_PATH should be the absolute path and name of the perl script
# interpreter (i.e. the result of `which perl').
PERL_PATH = /usr/bin/perl
#---------------------------------------------------------------------------
# Configuration options related to the dot tool
#---------------------------------------------------------------------------
# If the CLASS_DIAGRAMS tag is set to YES (the default) Doxygen will
# generate a inheritance diagram (in HTML, RTF and LaTeX) for classes with base
# or super classes. Setting the tag to NO turns the diagrams off. Note that
# this option also works with HAVE_DOT disabled, but it is recommended to
# install and use dot, since it yields more powerful graphs.
CLASS_DIAGRAMS = YES
# You can define message sequence charts within doxygen comments using the \msc
# command. Doxygen will then run the mscgen tool (see
# http://www.mcternan.me.uk/mscgen/) to produce the chart and insert it in the
# documentation. The MSCGEN_PATH tag allows you to specify the directory where
# the mscgen tool resides. If left empty the tool is assumed to be found in the
# default search path.
MSCGEN_PATH =
# If set to YES, the inheritance and collaboration graphs will hide
# inheritance and usage relations if the target is undocumented
# or is not a class.
HIDE_UNDOC_RELATIONS = YES
# If you set the HAVE_DOT tag to YES then doxygen will assume the dot tool is
# available from the path. This tool is part of Graphviz, a graph visualization
# toolkit from AT&T and Lucent Bell Labs. The other options in this section
# have no effect if this option is set to NO (the default)
HAVE_DOT = @HAVE_DOT@
# The DOT_NUM_THREADS specifies the number of dot invocations doxygen is
# allowed to run in parallel. When set to 0 (the default) doxygen will
# base this on the number of processors available in the system. You can set it
# explicitly to a value larger than 0 to get control over the balance
# between CPU load and processing speed.
DOT_NUM_THREADS = @MITK_DOXYGEN_DOT_NUM_THREADS@
# By default doxygen will use the Helvetica font for all dot files that
# doxygen generates. When you want a differently looking font you can specify
# the font name using DOT_FONTNAME. You need to make sure dot is able to find
# the font, which can be done by putting it in a standard location or by setting
# the DOTFONTPATH environment variable or by setting DOT_FONTPATH to the
# directory containing the font.
DOT_FONTNAME = FreeSans.ttf
# The DOT_FONTSIZE tag can be used to set the size of the font of dot graphs.
# The default size is 10pt.
DOT_FONTSIZE = 10
# By default doxygen will tell dot to use the Helvetica font.
# If you specify a different font using DOT_FONTNAME you can use DOT_FONTPATH to
# set the path where dot can find it.
DOT_FONTPATH =
# If the CLASS_GRAPH and HAVE_DOT tags are set to YES then doxygen
# will generate a graph for each documented class showing the direct and
# indirect inheritance relations. Setting this tag to YES will force the
# CLASS_DIAGRAMS tag to NO.
CLASS_GRAPH = YES
# If the COLLABORATION_GRAPH and HAVE_DOT tags are set to YES then doxygen
# will generate a graph for each documented class showing the direct and
# indirect implementation dependencies (inheritance, containment, and
# class references variables) of the class with other documented classes.
COLLABORATION_GRAPH = YES
# If the GROUP_GRAPHS and HAVE_DOT tags are set to YES then doxygen
# will generate a graph for groups, showing the direct groups dependencies
GROUP_GRAPHS = YES
# If the UML_LOOK tag is set to YES doxygen will generate inheritance and
# collaboration diagrams in a style similar to the OMG's Unified Modeling
# Language.
UML_LOOK = @MITK_DOXYGEN_UML_LOOK@
# If the UML_LOOK tag is enabled, the fields and methods are shown inside
# the class node. If there are many fields or methods and many nodes the
# graph may become too big to be useful. The UML_LIMIT_NUM_FIELDS
# threshold limits the number of items for each type to make the size more
# managable. Set this to 0 for no limit. Note that the threshold may be
# exceeded by 50% before the limit is enforced.
UML_LIMIT_NUM_FIELDS = 10
# If set to YES, the inheritance and collaboration graphs will show the
# relations between templates and their instances.
TEMPLATE_RELATIONS = YES
# If the ENABLE_PREPROCESSING, SEARCH_INCLUDES, INCLUDE_GRAPH, and HAVE_DOT
# tags are set to YES then doxygen will generate a graph for each documented
# file showing the direct and indirect include dependencies of the file with
# other documented files.
INCLUDE_GRAPH = NO
# If the ENABLE_PREPROCESSING, SEARCH_INCLUDES, INCLUDED_BY_GRAPH, and
# HAVE_DOT tags are set to YES then doxygen will generate a graph for each
# documented header file showing the documented files that directly or
# indirectly include this file.
INCLUDED_BY_GRAPH = NO
# If the CALL_GRAPH and HAVE_DOT options are set to YES then
# doxygen will generate a call dependency graph for every global function
# or class method. Note that enabling this option will significantly increase
# the time of a run. So in most cases it will be better to enable call graphs
# for selected functions only using the \callgraph command.
CALL_GRAPH = NO
# If the CALLER_GRAPH and HAVE_DOT tags are set to YES then
# doxygen will generate a caller dependency graph for every global function
# or class method. Note that enabling this option will significantly increase
# the time of a run. So in most cases it will be better to enable caller
# graphs for selected functions only using the \callergraph command.
CALLER_GRAPH = NO
# If the GRAPHICAL_HIERARCHY and HAVE_DOT tags are set to YES then doxygen
# will generate a graphical hierarchy of all classes instead of a textual one.
GRAPHICAL_HIERARCHY = NO
# If the DIRECTORY_GRAPH, SHOW_DIRECTORIES and HAVE_DOT tags are set to YES
# then doxygen will show the dependencies a directory has on other directories
# in a graphical way. The dependency relations are determined by the #include
# relations between the files in the directories.
DIRECTORY_GRAPH = YES
# The DOT_IMAGE_FORMAT tag can be used to set the image format of the images
# generated by dot. Possible values are svg, png, jpg, or gif.
# If left blank png will be used. If you choose svg you need to set
# HTML_FILE_EXTENSION to xhtml in order to make the SVG files
# visible in IE 9+ (other browsers do not have this requirement).
DOT_IMAGE_FORMAT = png
# If DOT_IMAGE_FORMAT is set to svg, then this option can be set to YES to
# enable generation of interactive SVG images that allow zooming and panning.
# Note that this requires a modern browser other than Internet Explorer.
# Tested and working are Firefox, Chrome, Safari, and Opera. For IE 9+ you
# need to set HTML_FILE_EXTENSION to xhtml in order to make the SVG files
# visible. Older versions of IE do not have SVG support.
INTERACTIVE_SVG = NO
# The tag DOT_PATH can be used to specify the path where the dot tool can be
# found. If left blank, it is assumed the dot tool can be found in the path.
DOT_PATH = @DOXYGEN_DOT_PATH@
# The DOTFILE_DIRS tag can be used to specify one or more directories that
# contain dot files that are included in the documentation (see the
# \dotfile command).
DOTFILE_DIRS =
# The MSCFILE_DIRS tag can be used to specify one or more directories that
# contain msc files that are included in the documentation (see the
# \mscfile command).
MSCFILE_DIRS =
# The DOT_GRAPH_MAX_NODES tag can be used to set the maximum number of
# nodes that will be shown in the graph. If the number of nodes in a graph
# becomes larger than this value, doxygen will truncate the graph, which is
# visualized by representing a node as a red box. Note that doxygen if the
# number of direct children of the root node in a graph is already larger than
# DOT_GRAPH_MAX_NODES then the graph will not be shown at all. Also note
# that the size of a graph can be further restricted by MAX_DOT_GRAPH_DEPTH.
DOT_GRAPH_MAX_NODES = 50
# The MAX_DOT_GRAPH_DEPTH tag can be used to set the maximum depth of the
# graphs generated by dot. A depth value of 3 means that only nodes reachable
# from the root by following a path via at most 3 edges will be shown. Nodes
# that lay further from the root node will be omitted. Note that setting this
# option to 1 or 2 may greatly reduce the computation time needed for large
# code bases. Also note that the size of a graph can be further restricted by
# DOT_GRAPH_MAX_NODES. Using a depth of 0 means no depth restriction.
MAX_DOT_GRAPH_DEPTH = 0
# Set the DOT_TRANSPARENT tag to YES to generate images with a transparent
# background. This is disabled by default, because dot on Windows does not
# seem to support this out of the box. Warning: Depending on the platform used,
# enabling this option may lead to badly anti-aliased labels on the edges of
# a graph (i.e. they become hard to read).
DOT_TRANSPARENT = NO
# Set the DOT_MULTI_TARGETS tag to YES allow dot to generate multiple output
# files in one run (i.e. multiple -o and -T options on the command line). This
# makes dot run faster, but since only newer versions of dot (>1.8.10)
# support this, this feature is disabled by default.
DOT_MULTI_TARGETS = NO
# If the GENERATE_LEGEND tag is set to YES (the default) Doxygen will
# generate a legend page explaining the meaning of the various boxes and
# arrows in the dot generated graphs.
GENERATE_LEGEND = YES
# If the DOT_CLEANUP tag is set to YES (the default) Doxygen will
# remove the intermediate dot files that are used to generate
# the various graphs.
DOT_CLEANUP = YES
diff --git a/Modules/ImageStatistics/CMakeLists.txt b/Modules/ImageStatistics/CMakeLists.txt
index 1e3f22a935..fe177d3216 100644
--- a/Modules/ImageStatistics/CMakeLists.txt
+++ b/Modules/ImageStatistics/CMakeLists.txt
@@ -1,11 +1,11 @@
MITK_CREATE_MODULE(
DEPENDS MitkImageExtraction MitkPlanarFigure
- PACKAGE_DEPENDS ITK|ITKVTK
+ PACKAGE_DEPENDS ITK|ITKVTK+ITKConvolution+ITKIOXML
WARNINGS_AS_ERRORS
)
if(BUILD_TESTING)
add_subdirectory(Testing)
endif(BUILD_TESTING)
diff --git a/Modules/ImageStatistics/Testing/CMakeLists.txt b/Modules/ImageStatistics/Testing/CMakeLists.txt
index c438117e4f..98f3654798 100644
--- a/Modules/ImageStatistics/Testing/CMakeLists.txt
+++ b/Modules/ImageStatistics/Testing/CMakeLists.txt
@@ -1 +1,34 @@
MITK_CREATE_MODULE_TESTS(EXTRA_DEPENDS MitkDICOMReader)
+
+mitkAddCustomModuleTest(mitkRoiMeasurementsTests mitkRoiMeasurementsTest ${MITK_DATA_DIR}/ImageStatisticsTestData/)
+
+file(GLOB allHotSpotTests RELATIVE "${CMAKE_CURRENT_SOURCE_DIR}/Data/Hotspot" "${CMAKE_CURRENT_SOURCE_DIR}/Data/Hotspot/*.xml")
+foreach(testcase ${allHotSpotTests})
+ string(REGEX REPLACE "[^a-zA-Z0-9_]" "_" testcaseName ${testcase})
+ mitkAddCustomModuleTest(mitkImageStatisticsHotspotTest_${testcaseName} mitkImageStatisticsHotspotTest ${CMAKE_CURRENT_SOURCE_DIR}/Data/Hotspot/${testcase})
+endforeach()
+
+#
+# The following lines may be activated to generate new test cases for mitkImageStatisticsHotspotTest.
+# Test cases are generated by mitkMultiGaussianTest. All .xml files in Data/TestGeneration/Input will
+# be processed and transformed into new .xml files containing statistics in Data/TestGeneration/Output.
+#
+if (false)
+ set(testInputDir ${CMAKE_CURRENT_SOURCE_DIR}/Data/TestGeneration/Input)
+ set(testOutputDir ${CMAKE_CURRENT_SOURCE_DIR}/Data/TestGeneration/Output)
+ file(GLOB testcasesToGenerate RELATIVE "${testInputDir}" "${testInputDir}/*.xml")
+
+ if (NOT EXISTS ${testOutputDir})
+ file(MAKE_DIRECTORY ${testOutputDir})
+ endif()
+
+ foreach(testinput ${testcasesToGenerate})
+ string(REGEX REPLACE "[^a-zA-Z0-9_]\\+" "_" testcaseName ${testinput})
+ string(REGEX REPLACE "\\.xml" "" testoutput ${testinput})
+ message("Generate hotspot test case '${testinput}'. Output in '${testoutput}.xml' and '${testoutput}.nrrd'")
+ mitkAddCustomModuleTest(mitkMultiGaussianTest_${testcaseName}
+ mitkMultiGaussianTest
+ ${testOutputDir}/${testoutput}
+ ${testInputDir}/${testinput})
+ endforeach()
+endif()
diff --git a/Modules/ImageStatistics/Testing/Data/Hotspot/GlobalPeakOutsideSegmentation_10_20.xml b/Modules/ImageStatistics/Testing/Data/Hotspot/GlobalPeakOutsideSegmentation_10_20.xml
new file mode 100644
index 0000000000..ae19e71c63
--- /dev/null
+++ b/Modules/ImageStatistics/Testing/Data/Hotspot/GlobalPeakOutsideSegmentation_10_20.xml
@@ -0,0 +1,10 @@
+
+
+
+
+
+
+
+
+
+
diff --git a/Modules/ImageStatistics/Testing/Data/Hotspot/GlobalPeakOutsideSegmentation_25_30.xml b/Modules/ImageStatistics/Testing/Data/Hotspot/GlobalPeakOutsideSegmentation_25_30.xml
new file mode 100644
index 0000000000..0d3e2d2590
--- /dev/null
+++ b/Modules/ImageStatistics/Testing/Data/Hotspot/GlobalPeakOutsideSegmentation_25_30.xml
@@ -0,0 +1,10 @@
+
+
+
+
+
+
+
+
+
+
diff --git a/Modules/ImageStatistics/Testing/Data/Hotspot/GlobalPeakOutsideSegmentation_40_30.xml b/Modules/ImageStatistics/Testing/Data/Hotspot/GlobalPeakOutsideSegmentation_40_30.xml
new file mode 100644
index 0000000000..a27278818b
--- /dev/null
+++ b/Modules/ImageStatistics/Testing/Data/Hotspot/GlobalPeakOutsideSegmentation_40_30.xml
@@ -0,0 +1,10 @@
+
+
+
+
+
+
+
+
+
+
diff --git a/Modules/ImageStatistics/Testing/Data/Hotspot/MaxOutsidePeak_10_20.xml b/Modules/ImageStatistics/Testing/Data/Hotspot/MaxOutsidePeak_10_20.xml
new file mode 100644
index 0000000000..df5300c886
--- /dev/null
+++ b/Modules/ImageStatistics/Testing/Data/Hotspot/MaxOutsidePeak_10_20.xml
@@ -0,0 +1,10 @@
+
+
+
+
+
+
+
+
+
+
diff --git a/Modules/ImageStatistics/Testing/Data/Hotspot/MaxOutsidePeak_25_30.xml b/Modules/ImageStatistics/Testing/Data/Hotspot/MaxOutsidePeak_25_30.xml
new file mode 100644
index 0000000000..9e6fa1c8f4
--- /dev/null
+++ b/Modules/ImageStatistics/Testing/Data/Hotspot/MaxOutsidePeak_25_30.xml
@@ -0,0 +1,11 @@
+
+
+
+
+
+
+
+
+
+
+
diff --git a/Modules/ImageStatistics/Testing/Data/Hotspot/MaxOutsidePeak_40_30.xml b/Modules/ImageStatistics/Testing/Data/Hotspot/MaxOutsidePeak_40_30.xml
new file mode 100644
index 0000000000..09aa3fadc3
--- /dev/null
+++ b/Modules/ImageStatistics/Testing/Data/Hotspot/MaxOutsidePeak_40_30.xml
@@ -0,0 +1,10 @@
+
+
+
+
+
+
+
+
+
+
diff --git a/Modules/ImageStatistics/Testing/Data/Hotspot/PeakInMaxOutsideSegmentation_10_20.xml b/Modules/ImageStatistics/Testing/Data/Hotspot/PeakInMaxOutsideSegmentation_10_20.xml
new file mode 100644
index 0000000000..acdf3d3b11
--- /dev/null
+++ b/Modules/ImageStatistics/Testing/Data/Hotspot/PeakInMaxOutsideSegmentation_10_20.xml
@@ -0,0 +1,9 @@
+
+
+
+
+
+
+
+
+
diff --git a/Modules/ImageStatistics/Testing/Data/Hotspot/PeakInMaxOutsideSegmentation_25_30.xml b/Modules/ImageStatistics/Testing/Data/Hotspot/PeakInMaxOutsideSegmentation_25_30.xml
new file mode 100644
index 0000000000..df12f187ac
--- /dev/null
+++ b/Modules/ImageStatistics/Testing/Data/Hotspot/PeakInMaxOutsideSegmentation_25_30.xml
@@ -0,0 +1,11 @@
+
+
+
+
+
+
+
+
+
+
+
diff --git a/Modules/ImageStatistics/Testing/Data/Hotspot/PeakInMaxOutsideSegmentation_40_30.xml b/Modules/ImageStatistics/Testing/Data/Hotspot/PeakInMaxOutsideSegmentation_40_30.xml
new file mode 100644
index 0000000000..0440a5ecb6
--- /dev/null
+++ b/Modules/ImageStatistics/Testing/Data/Hotspot/PeakInMaxOutsideSegmentation_40_30.xml
@@ -0,0 +1,9 @@
+
+
+
+
+
+
+
+
+
diff --git a/Modules/ImageStatistics/Testing/Data/Hotspot/PeakNearBorder_10_20.xml b/Modules/ImageStatistics/Testing/Data/Hotspot/PeakNearBorder_10_20.xml
new file mode 100644
index 0000000000..2c2345627c
--- /dev/null
+++ b/Modules/ImageStatistics/Testing/Data/Hotspot/PeakNearBorder_10_20.xml
@@ -0,0 +1,12 @@
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/Modules/ImageStatistics/Testing/Data/Hotspot/PeakNearBorder_25_30.xml b/Modules/ImageStatistics/Testing/Data/Hotspot/PeakNearBorder_25_30.xml
new file mode 100644
index 0000000000..4200ead9a2
--- /dev/null
+++ b/Modules/ImageStatistics/Testing/Data/Hotspot/PeakNearBorder_25_30.xml
@@ -0,0 +1,10 @@
+
+
+
+
+
+
+
+
+
+
diff --git a/Modules/ImageStatistics/Testing/Data/Hotspot/PeakNearBorder_40_30.xml b/Modules/ImageStatistics/Testing/Data/Hotspot/PeakNearBorder_40_30.xml
new file mode 100644
index 0000000000..224c52e4d9
--- /dev/null
+++ b/Modules/ImageStatistics/Testing/Data/Hotspot/PeakNearBorder_40_30.xml
@@ -0,0 +1,10 @@
+
+
+
+
+
+
+
+
+
+
diff --git a/Modules/ImageStatistics/Testing/Data/Hotspot/TwoSegmentations_10_20.xml b/Modules/ImageStatistics/Testing/Data/Hotspot/TwoSegmentations_10_20.xml
new file mode 100644
index 0000000000..44d38d211f
--- /dev/null
+++ b/Modules/ImageStatistics/Testing/Data/Hotspot/TwoSegmentations_10_20.xml
@@ -0,0 +1,13 @@
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/Modules/ImageStatistics/Testing/Data/Hotspot/TwoSegmentations_25_30.xml b/Modules/ImageStatistics/Testing/Data/Hotspot/TwoSegmentations_25_30.xml
new file mode 100644
index 0000000000..d9121d7f24
--- /dev/null
+++ b/Modules/ImageStatistics/Testing/Data/Hotspot/TwoSegmentations_25_30.xml
@@ -0,0 +1,13 @@
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/Modules/ImageStatistics/Testing/Data/Hotspot/TwoSegmentations_40_30.xml b/Modules/ImageStatistics/Testing/Data/Hotspot/TwoSegmentations_40_30.xml
new file mode 100644
index 0000000000..15d45e0420
--- /dev/null
+++ b/Modules/ImageStatistics/Testing/Data/Hotspot/TwoSegmentations_40_30.xml
@@ -0,0 +1,12 @@
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/Modules/ImageStatistics/Testing/Data/neue Bilder/Hotspot_Case1.xml b/Modules/ImageStatistics/Testing/Data/neue Bilder/Hotspot_Case1.xml
new file mode 100644
index 0000000000..e57655f2d1
--- /dev/null
+++ b/Modules/ImageStatistics/Testing/Data/neue Bilder/Hotspot_Case1.xml
@@ -0,0 +1,7 @@
+
+
+
+
+
+
+
diff --git a/Modules/ImageStatistics/Testing/Data/neue Bilder/Hotspot_Case2.xml b/Modules/ImageStatistics/Testing/Data/neue Bilder/Hotspot_Case2.xml
new file mode 100644
index 0000000000..088d464625
--- /dev/null
+++ b/Modules/ImageStatistics/Testing/Data/neue Bilder/Hotspot_Case2.xml
@@ -0,0 +1,7 @@
+
+
+
+
+
+
+
diff --git a/Modules/ImageStatistics/Testing/Data/neue Bilder/Hotspot_Case3.xml b/Modules/ImageStatistics/Testing/Data/neue Bilder/Hotspot_Case3.xml
new file mode 100644
index 0000000000..8bd11ad0c4
--- /dev/null
+++ b/Modules/ImageStatistics/Testing/Data/neue Bilder/Hotspot_Case3.xml
@@ -0,0 +1,7 @@
+
+
+
+
+
+
+
diff --git a/Modules/ImageStatistics/Testing/Data/neue Bilder/Hotspot_Case4.xml b/Modules/ImageStatistics/Testing/Data/neue Bilder/Hotspot_Case4.xml
new file mode 100644
index 0000000000..438ae152c1
--- /dev/null
+++ b/Modules/ImageStatistics/Testing/Data/neue Bilder/Hotspot_Case4.xml
@@ -0,0 +1,7 @@
+
+
+
+
+
+
+
diff --git a/Modules/ImageStatistics/Testing/Data/neue Bilder/Hotspot_Case5.xml b/Modules/ImageStatistics/Testing/Data/neue Bilder/Hotspot_Case5.xml
new file mode 100644
index 0000000000..3657c60064
--- /dev/null
+++ b/Modules/ImageStatistics/Testing/Data/neue Bilder/Hotspot_Case5.xml
@@ -0,0 +1,7 @@
+
+
+
+
+
+
+
diff --git a/Modules/ImageStatistics/Testing/Data/neue Bilder/Hotspot_Case6.xml b/Modules/ImageStatistics/Testing/Data/neue Bilder/Hotspot_Case6.xml
new file mode 100644
index 0000000000..ecc58a523b
--- /dev/null
+++ b/Modules/ImageStatistics/Testing/Data/neue Bilder/Hotspot_Case6.xml
@@ -0,0 +1,7 @@
+
+
+
+
+
+
+
diff --git a/Modules/ImageStatistics/Testing/Data/neue Bilder/Hotspot_Case7.xml b/Modules/ImageStatistics/Testing/Data/neue Bilder/Hotspot_Case7.xml
new file mode 100644
index 0000000000..0ac9a6c591
--- /dev/null
+++ b/Modules/ImageStatistics/Testing/Data/neue Bilder/Hotspot_Case7.xml
@@ -0,0 +1,7 @@
+
+
+
+
+
+
+
diff --git a/Modules/ImageStatistics/Testing/Data/neue Bilder/Hotspot_Case8.xml b/Modules/ImageStatistics/Testing/Data/neue Bilder/Hotspot_Case8.xml
new file mode 100644
index 0000000000..37d5cf1cec
--- /dev/null
+++ b/Modules/ImageStatistics/Testing/Data/neue Bilder/Hotspot_Case8.xml
@@ -0,0 +1,7 @@
+
+
+
+
+
+
+
diff --git a/Modules/ImageStatistics/Testing/Data/neue Bilder/Hotspot_Case9.xml b/Modules/ImageStatistics/Testing/Data/neue Bilder/Hotspot_Case9.xml
new file mode 100644
index 0000000000..f234557dc1
--- /dev/null
+++ b/Modules/ImageStatistics/Testing/Data/neue Bilder/Hotspot_Case9.xml
@@ -0,0 +1,7 @@
+
+
+
+
+
+
+
diff --git a/Modules/ImageStatistics/Testing/files.cmake b/Modules/ImageStatistics/Testing/files.cmake
index 01792788aa..6cbda61dfe 100644
--- a/Modules/ImageStatistics/Testing/files.cmake
+++ b/Modules/ImageStatistics/Testing/files.cmake
@@ -1,5 +1,10 @@
set(MODULE_TESTS
mitkImageStatisticsCalculatorTest.cpp
mitkPointSetStatisticsCalculatorTest.cpp
mitkPointSetDifferenceStatisticsCalculatorTest.cpp
)
+
+set(MODULE_CUSTOM_TESTS
+ mitkImageStatisticsHotspotTest.cpp
+# mitkMultiGaussianTest.cpp # TODO: activate test to generate new test cases for mitkImageStatisticsHotspotTest
+)
diff --git a/Modules/ImageStatistics/Testing/mitkImageStatisticsCalculatorTest.cpp b/Modules/ImageStatistics/Testing/mitkImageStatisticsCalculatorTest.cpp
index c02422b7af..69d7a086a9 100644
--- a/Modules/ImageStatistics/Testing/mitkImageStatisticsCalculatorTest.cpp
+++ b/Modules/ImageStatistics/Testing/mitkImageStatisticsCalculatorTest.cpp
@@ -1,418 +1,418 @@
/*===================================================================
The Medical Imaging Interaction Toolkit (MITK)
Copyright (c) German Cancer Research Center,
Division of Medical and Biological Informatics.
All rights reserved.
This software is distributed WITHOUT ANY WARRANTY; without
even the implied warranty of MERCHANTABILITY or FITNESS FOR
A PARTICULAR PURPOSE.
See LICENSE.txt or http://www.mitk.org for details.
===================================================================*/
#include "mitkTestFixture.h"
#include "mitkTestingMacros.h"
#include "mitkImageStatisticsCalculator.h"
#include "mitkPlanarPolygon.h"
#include "mitkClassicDICOMSeriesReader.h"
#include "vtkStreamingDemandDrivenPipeline.h"
#include
#include
/**
* \brief Test class for mitkImageStatisticsCalculator
*
* This test covers:
* - instantiation of an ImageStatisticsCalculator class
* - correctness of statistics when using PlanarFigures for masking
*/
class mitkImageStatisticsCalculatorTestSuite : public mitk::TestFixture
{
CPPUNIT_TEST_SUITE(mitkImageStatisticsCalculatorTestSuite);
MITK_TEST(TestUninitializedImage);
MITK_TEST(TestCase1);
MITK_TEST(TestCase2);
MITK_TEST(TestCase3);
MITK_TEST(TestCase4);
MITK_TEST(TestCase5);
MITK_TEST(TestCase6);
MITK_TEST(TestCase7);
MITK_TEST(TestCase8);
MITK_TEST(TestCase9);
MITK_TEST(TestCase10);
MITK_TEST(TestCase11);
MITK_TEST(TestCase12);
CPPUNIT_TEST_SUITE_END();
public:
void setUp();
void TestUninitializedImage();
void TestCase1();
void TestCase2();
void TestCase3();
void TestCase4();
void TestCase5();
void TestCase6();
void TestCase7();
void TestCase8();
void TestCase9();
void TestCase10();
void TestCase11();
void TestCase12();
private:
mitk::Image::Pointer m_Image;
mitk::PlaneGeometry::Pointer m_Geometry;
// calculate statistics for the given image and planarpolygon
const mitk::ImageStatisticsCalculator::Statistics ComputeStatistics( mitk::Image::Pointer image,
mitk::PlanarFigure::Pointer polygon );
void VerifyStatistics(const mitk::ImageStatisticsCalculator::Statistics& stats,
double testMean, double testSD);
};
void mitkImageStatisticsCalculatorTestSuite::setUp()
{
std::string filename = this->GetTestDataFilePath("ImageStatistics/testimage.dcm");
if (filename.empty())
{
MITK_TEST_FAILED_MSG( << "Could not find test file" )
}
MITK_TEST_OUTPUT(<< "Loading test image '" << filename << "'")
mitk::StringList files;
files.push_back( filename );
mitk::ClassicDICOMSeriesReader::Pointer reader = mitk::ClassicDICOMSeriesReader::New();
reader->SetInputFiles( files );
reader->AnalyzeInputFiles();
reader->LoadImages();
MITK_TEST_CONDITION_REQUIRED( reader->GetNumberOfOutputs() == 1, "Loaded one result from file" );
m_Image = reader->GetOutput(0).GetMitkImage();
MITK_TEST_CONDITION_REQUIRED( m_Image.IsNotNull(), "Loaded an mitk::Image" );
m_Geometry = m_Image->GetSlicedGeometry()->GetPlaneGeometry(0);
MITK_TEST_CONDITION_REQUIRED( m_Geometry.IsNotNull(), "Getting image geometry" )
}
void mitkImageStatisticsCalculatorTestSuite::TestCase1()
{
/*****************************
* one whole white pixel
* -> mean of 255 expected
******************************/
mitk::PlanarPolygon::Pointer figure1 = mitk::PlanarPolygon::New();
figure1->SetPlaneGeometry( m_Geometry );
mitk::Point2D pnt1; pnt1[0] = 10.5 ; pnt1[1] = 3.5;
figure1->PlaceFigure( pnt1 );
mitk::Point2D pnt2; pnt2[0] = 9.5; pnt2[1] = 3.5;
figure1->SetControlPoint( 1, pnt2, true );
mitk::Point2D pnt3; pnt3[0] = 9.5; pnt3[1] = 4.5;
figure1->SetControlPoint( 2, pnt3, true );
mitk::Point2D pnt4; pnt4[0] = 10.5; pnt4[1] = 4.5;
figure1->SetControlPoint( 3, pnt4, true );
figure1->GetPolyLine(0);
this->VerifyStatistics(ComputeStatistics(m_Image, figure1.GetPointer()), 255.0, 0.0);
}
void mitkImageStatisticsCalculatorTestSuite::TestCase2()
{
/*****************************
* half pixel in x-direction (white)
* -> mean of 255 expected
******************************/
mitk::PlanarPolygon::Pointer figure1 = mitk::PlanarPolygon::New();
figure1->SetPlaneGeometry( m_Geometry );
mitk::Point2D pnt1; pnt1[0] = 10.0 ; pnt1[1] = 3.5;
figure1->PlaceFigure( pnt1 );
mitk::Point2D pnt2; pnt2[0] = 9.5; pnt2[1] = 3.5;
figure1->SetControlPoint( 1, pnt2, true );
mitk::Point2D pnt3; pnt3[0] = 9.5; pnt3[1] = 4.5;
figure1->SetControlPoint( 2, pnt3, true );
mitk::Point2D pnt4; pnt4[0] = 10.0; pnt4[1] = 4.5;
figure1->SetControlPoint( 3, pnt4, true );
figure1->GetPolyLine(0);
this->VerifyStatistics(ComputeStatistics(m_Image, figure1.GetPointer()), 255.0, 0.0);
}
void mitkImageStatisticsCalculatorTestSuite::TestCase3()
{
/*****************************
* half pixel in diagonal-direction (white)
* -> mean of 255 expected
******************************/
mitk::PlanarPolygon::Pointer figure1 = mitk::PlanarPolygon::New();
figure1->SetPlaneGeometry( m_Geometry );
mitk::Point2D pnt1; pnt1[0] = 10.5 ; pnt1[1] = 3.5;
figure1->PlaceFigure( pnt1 );
mitk::Point2D pnt2; pnt2[0] = 9.5; pnt2[1] = 3.5;
figure1->SetControlPoint( 1, pnt2, true );
mitk::Point2D pnt3; pnt3[0] = 9.5; pnt3[1] = 4.5;
figure1->SetControlPoint( 2, pnt3, true );
figure1->GetPolyLine(0);
this->VerifyStatistics(ComputeStatistics(m_Image, figure1.GetPointer()), 255.0, 0.0);
}
void mitkImageStatisticsCalculatorTestSuite::TestCase4()
{
/*****************************
* one pixel (white) + 2 half pixels (white) + 1 half pixel (black)
* -> mean of 191.25 expected
******************************/
mitk::PlanarPolygon::Pointer figure1 = mitk::PlanarPolygon::New();
figure1->SetPlaneGeometry( m_Geometry );
mitk::Point2D pnt1; pnt1[0] = 1.1; pnt1[1] = 1.1;
figure1->PlaceFigure( pnt1 );
mitk::Point2D pnt2; pnt2[0] = 2.0; pnt2[1] = 2.0;
figure1->SetControlPoint( 1, pnt2, true );
mitk::Point2D pnt3; pnt3[0] = 3.0; pnt3[1] = 1.0;
figure1->SetControlPoint( 2, pnt3, true );
mitk::Point2D pnt4; pnt4[0] = 2.0; pnt4[1] = 0.0;
figure1->SetControlPoint( 3, pnt4, true );
figure1->GetPolyLine(0);
this->VerifyStatistics(ComputeStatistics(m_Image, figure1.GetPointer()), 191.25, 127.5);
}
void mitkImageStatisticsCalculatorTestSuite::TestCase5()
{
/*****************************
* whole pixel (white) + half pixel (gray) in x-direction
* -> mean of 191.5 expected
******************************/
mitk::PlanarPolygon::Pointer figure1 = mitk::PlanarPolygon::New();
figure1->SetPlaneGeometry( m_Geometry );
mitk::Point2D pnt1; pnt1[0] = 11.0; pnt1[1] = 3.5;
figure1->PlaceFigure( pnt1 );
mitk::Point2D pnt2; pnt2[0] = 9.5; pnt2[1] = 3.5;
figure1->SetControlPoint( 1, pnt2, true );
mitk::Point2D pnt3; pnt3[0] = 9.5; pnt3[1] = 4.5;
figure1->SetControlPoint( 2, pnt3, true );
mitk::Point2D pnt4; pnt4[0] = 11.0; pnt4[1] = 4.5;
figure1->SetControlPoint( 3, pnt4, true );
figure1->GetPolyLine(0);
this->VerifyStatistics(ComputeStatistics(m_Image, figure1.GetPointer()), 191.50, 89.80);
}
void mitkImageStatisticsCalculatorTestSuite::TestCase6()
{
/*****************************
* quarter pixel (black) + whole pixel (white) + half pixel (gray) in x-direction
* -> mean of 191.5 expected
******************************/
mitk::PlanarPolygon::Pointer figure1 = mitk::PlanarPolygon::New();
figure1->SetPlaneGeometry( m_Geometry );
mitk::Point2D pnt1; pnt1[0] = 11.0; pnt1[1] = 3.5;
figure1->PlaceFigure( pnt1 );
mitk::Point2D pnt2; pnt2[0] = 9.25; pnt2[1] = 3.5;
figure1->SetControlPoint( 1, pnt2, true );
mitk::Point2D pnt3; pnt3[0] = 9.25; pnt3[1] = 4.5;
figure1->SetControlPoint( 2, pnt3, true );
mitk::Point2D pnt4; pnt4[0] = 11.0; pnt4[1] = 4.5;
figure1->SetControlPoint( 3, pnt4, true );
figure1->GetPolyLine(0);
this->VerifyStatistics(ComputeStatistics(m_Image, figure1.GetPointer()), 191.5, 89.80);
}
void mitkImageStatisticsCalculatorTestSuite::TestCase7()
{
/*****************************
* half pixel (black) + whole pixel (white) + half pixel (gray) in x-direction
* -> mean of 127.66 expected
******************************/
mitk::PlanarPolygon::Pointer figure1 = mitk::PlanarPolygon::New();
figure1->SetPlaneGeometry( m_Geometry );
mitk::Point2D pnt1; pnt1[0] = 11.0; pnt1[1] = 3.5;
figure1->PlaceFigure( pnt1 );
mitk::Point2D pnt2; pnt2[0] = 9.0; pnt2[1] = 3.5;
figure1->SetControlPoint( 1, pnt2, true );
mitk::Point2D pnt3; pnt3[0] = 9.0; pnt3[1] = 4.0;
figure1->SetControlPoint( 2, pnt3, true );
mitk::Point2D pnt4; pnt4[0] = 11.0; pnt4[1] = 4.0;
figure1->SetControlPoint( 3, pnt4, true );
figure1->GetPolyLine(0);
this->VerifyStatistics(ComputeStatistics(m_Image, figure1.GetPointer()), 127.66, 127.5);
}
void mitkImageStatisticsCalculatorTestSuite::TestCase8()
{
/*****************************
* whole pixel (gray)
* -> mean of 128 expected
******************************/
mitk::PlanarPolygon::Pointer figure2 = mitk::PlanarPolygon::New();
figure2->SetPlaneGeometry( m_Geometry );
mitk::Point2D pnt1; pnt1[0] = 11.5; pnt1[1] = 10.5;
figure2->PlaceFigure( pnt1 );
mitk::Point2D pnt2; pnt2[0] = 11.5; pnt2[1] = 11.5;
figure2->SetControlPoint( 1, pnt2, true );
mitk::Point2D pnt3; pnt3[0] = 12.5; pnt3[1] = 11.5;
figure2->SetControlPoint( 2, pnt3, true );
mitk::Point2D pnt4; pnt4[0] = 12.5; pnt4[1] = 10.5;
figure2->SetControlPoint( 3, pnt4, true );
figure2->GetPolyLine(0);
this->VerifyStatistics(ComputeStatistics(m_Image, figure2.GetPointer()), 128.0, 0.0);
}
void mitkImageStatisticsCalculatorTestSuite::TestCase9()
{
/*****************************
* whole pixel (gray) + half pixel (white) in y-direction
* -> mean of 191.5 expected
******************************/
mitk::PlanarPolygon::Pointer figure2 = mitk::PlanarPolygon::New();
figure2->SetPlaneGeometry( m_Geometry );
mitk::Point2D pnt1; pnt1[0] = 11.5; pnt1[1] = 10.5;
figure2->PlaceFigure( pnt1 );
mitk::Point2D pnt2; pnt2[0] = 11.5; pnt2[1] = 12.0;
figure2->SetControlPoint( 1, pnt2, true );
mitk::Point2D pnt3; pnt3[0] = 12.5; pnt3[1] = 12.0;
figure2->SetControlPoint( 2, pnt3, true );
mitk::Point2D pnt4; pnt4[0] = 12.5; pnt4[1] = 10.5;
figure2->SetControlPoint( 3, pnt4, true );
figure2->GetPolyLine(0);
this->VerifyStatistics(ComputeStatistics(m_Image, figure2.GetPointer()), 191.5, 89.80);
}
void mitkImageStatisticsCalculatorTestSuite::TestCase10()
{
/*****************************
* 2 whole pixel (white) + 2 whole pixel (black) in y-direction
* -> mean of 127.66 expected
******************************/
mitk::PlanarPolygon::Pointer figure2 = mitk::PlanarPolygon::New();
figure2->SetPlaneGeometry( m_Geometry );
mitk::Point2D pnt1; pnt1[0] = 11.5; pnt1[1] = 10.5;
figure2->PlaceFigure( pnt1 );
mitk::Point2D pnt2; pnt2[0] = 11.5; pnt2[1] = 13.5;
figure2->SetControlPoint( 1, pnt2, true );
mitk::Point2D pnt3; pnt3[0] = 12.5; pnt3[1] = 13.5;
figure2->SetControlPoint( 2, pnt3, true );
mitk::Point2D pnt4; pnt4[0] = 12.5; pnt4[1] = 10.5;
figure2->SetControlPoint( 3, pnt4, true );
figure2->GetPolyLine(0);
this->VerifyStatistics(ComputeStatistics(m_Image, figure2.GetPointer()), 127.66, 127.5);
}
void mitkImageStatisticsCalculatorTestSuite::TestCase11()
{
/*****************************
* 9 whole pixels (white) + 3 half pixels (white)
* + 3 whole pixel (black) [ + 3 slightly less than half pixels (black)]
* -> mean of 204.0 expected
******************************/
mitk::PlanarPolygon::Pointer figure2 = mitk::PlanarPolygon::New();
figure2->SetPlaneGeometry( m_Geometry );
mitk::Point2D pnt1; pnt1[0] = 0.5; pnt1[1] = 0.5;
figure2->PlaceFigure( pnt1 );
mitk::Point2D pnt2; pnt2[0] = 3.5; pnt2[1] = 3.5;
figure2->SetControlPoint( 1, pnt2, true );
mitk::Point2D pnt3; pnt3[0] = 8.4999; pnt3[1] = 3.5;
figure2->SetControlPoint( 2, pnt3, true );
mitk::Point2D pnt4; pnt4[0] = 5.4999; pnt4[1] = 0.5;
figure2->SetControlPoint( 3, pnt4, true );
figure2->GetPolyLine(0);
this->VerifyStatistics(ComputeStatistics(m_Image, figure2.GetPointer()), 204.0, 105.58 );
}
void mitkImageStatisticsCalculatorTestSuite::TestCase12()
{
/*****************************
* half pixel (white) + whole pixel (white) + half pixel (black)
* -> mean of 212.66 expected
******************************/
mitk::PlanarPolygon::Pointer figure2 = mitk::PlanarPolygon::New();
figure2->SetPlaneGeometry( m_Geometry );
mitk::Point2D pnt1; pnt1[0] = 9.5; pnt1[1] = 0.5;
figure2->PlaceFigure( pnt1 );
mitk::Point2D pnt2; pnt2[0] = 9.5; pnt2[1] = 2.5;
figure2->SetControlPoint( 1, pnt2, true );
mitk::Point2D pnt3; pnt3[0] = 11.5; pnt3[1] = 2.5;
figure2->SetControlPoint( 2, pnt3, true );
figure2->GetPolyLine(0);
this->VerifyStatistics(ComputeStatistics(m_Image, figure2.GetPointer()), 212.66, 73.32);
}
const mitk::ImageStatisticsCalculator::Statistics
mitkImageStatisticsCalculatorTestSuite::ComputeStatistics( mitk::Image::Pointer image, mitk::PlanarFigure::Pointer polygon )
{
mitk::ImageStatisticsCalculator::Pointer statisticsCalculator = mitk::ImageStatisticsCalculator::New();
statisticsCalculator->SetImage( image );
statisticsCalculator->SetMaskingModeToPlanarFigure();
statisticsCalculator->SetPlanarFigure( polygon );
statisticsCalculator->ComputeStatistics();
return statisticsCalculator->GetStatistics();
}
void mitkImageStatisticsCalculatorTestSuite::VerifyStatistics(const mitk::ImageStatisticsCalculator::Statistics& stats,
double testMean, double testSD)
{
- int tmpMean = stats.Mean * 100;
+ int tmpMean = stats.GetMean() * 100;
double calculatedMean = tmpMean / 100.0;
MITK_TEST_CONDITION( calculatedMean == testMean,
"Calculated mean grayvalue '" << calculatedMean <<
"' is equal to the desired value '" << testMean << "'" );
- int tmpSD = stats.Sigma * 100;
+ int tmpSD = stats.GetSigma() * 100;
double calculatedSD = tmpSD / 100.0;
MITK_TEST_CONDITION( calculatedSD == testSD,
"Calculated grayvalue sd '" << calculatedSD <<
"' is equal to the desired value '" << testSD <<"'" );
}
void mitkImageStatisticsCalculatorTestSuite::TestUninitializedImage()
{
/*****************************
* loading uninitialized image to datastorage
******************************/
MITK_TEST_FOR_EXCEPTION_BEGIN(mitk::Exception)
mitk::Image::Pointer image = mitk::Image::New();
mitk::DataNode::Pointer node = mitk::DataNode::New();
node->SetData(image);
mitk::ImageStatisticsCalculator::Pointer is = mitk::ImageStatisticsCalculator::New();
is->ComputeStatistics();
MITK_TEST_FOR_EXCEPTION_END(mitk::Exception)
}
MITK_TEST_SUITE_REGISTRATION(mitkImageStatisticsCalculator)
diff --git a/Modules/ImageStatistics/Testing/mitkImageStatisticsHotspotTest.cpp b/Modules/ImageStatistics/Testing/mitkImageStatisticsHotspotTest.cpp
new file mode 100644
index 0000000000..4a0b263111
--- /dev/null
+++ b/Modules/ImageStatistics/Testing/mitkImageStatisticsHotspotTest.cpp
@@ -0,0 +1,632 @@
+/*===================================================================
+
+The Medical Imaging Interaction Toolkit (MITK)
+
+Copyright (c) German Cancer Research Center,
+Division of Medical and Biological Informatics.
+All rights reserved.
+
+This software is distributed WITHOUT ANY WARRANTY; without
+even the implied warranty of MERCHANTABILITY or FITNESS FOR
+A PARTICULAR PURPOSE.
+
+See LICENSE.txt or http://www.mitk.org for details.
+
+===================================================================*/
+
+#include "mitkImageStatisticsCalculator.h"
+#include "itkMultiGaussianImageSource.h"
+#include "mitkTestingMacros.h"
+#include "mitkImageCast.h"
+
+#include
+
+#include
+
+#include
+#include
+
+/**
+ \section hotspotCalculationTestCases Testcases
+
+ To see the different Hotspot-Testcases have a look at the \ref hotspottestdoc.
+
+ Note from an intensive session of checking the test results:
+ - itk::MultiGaussianImageSource needs a review
+ - the test idea is ok, but the combination of XML files for parameters and MultiGaussianImageSource has serious flaws
+ - the XML file should contain exactly the parameters that MultiGaussianImageSource requires
+ - in contrast, now the XML file mentions index coordinates for gaussian centers while the MultiGaussianImageSource expects world coordinates
+ - this requires a transformation (index * spacing assuming no rotation) that was actually broken until recently
+*/
+
+struct mitkImageStatisticsHotspotTestClass
+{
+ /**
+ \brief Test parameters for one test case.
+
+ Describes all aspects of a single test case:
+ - parameters to generate a test image
+ - parameters of a ROI that describes where to calculate statistics
+ - expected statistics results
+ */
+ struct Parameters
+ {
+ public:
+
+ // XML-Tag
+
+ /** \brief XML-Tag "image-rows": size of x-dimension */
+ int m_ImageRows;
+ /** \brief XML-Tag "image-columns": size of y-dimension */
+ int m_ImageColumns;
+ /** \brief XML-Tag "image-slices": size of z-dimension */
+ int m_ImageSlices;
+ /** \brief XML-Tag "numberOfGaussians": number of used gauss-functions */
+ int m_NumberOfGaussian;
+
+ /** \brief XML-Tags "spacingX", "spacingY", "spacingZ": spacing of image in every direction */
+ double m_Spacing[3];
+
+ /** \brief XML-Tag "entireHotSpotInImage" */
+ unsigned int m_EntireHotspotInImage;
+
+ // XML-Tag
+
+ /**
+ \brief XML-Tag "centerIndexX: gaussian parameter
+ \warning This parameter READS the centerIndexX parameter from file and is THEN MISUSED to calculate some position in world coordinates, so we require double.
+ */
+ std::vector m_CenterX;
+ /** \brief XML-Tag "centerIndexY: gaussian parameter
+ \warning This parameter READS the centerIndexX parameter from file and is THEN MISUSED to calculate some position in world coordinates, so we require double.
+ */
+ std::vector m_CenterY;
+ /** \brief XML-Tag "centerIndexZ: gaussian parameter
+ \warning This parameter READS the centerIndexX parameter from file and is THEN MISUSED to calculate some position in world coordinates, so we require double.
+ */
+ std::vector m_CenterZ;
+
+ /** \brief XML-Tag "deviationX: gaussian parameter */
+ std::vector m_SigmaX;
+ /** \brief XML-Tag "deviationY: gaussian parameter */
+ std::vector m_SigmaY;
+ /** \brief XML-Tag "deviationZ: gaussian parameter */
+ std::vector m_SigmaZ;
+
+ /** \brief XML-Tag "altitude: gaussian parameter */
+ std::vector m_Altitude;
+
+ // XML-Tag
+
+ /** \brief XML-Tag "numberOfLabels": number of different labels which appear in the mask */
+ unsigned int m_NumberOfLabels;
+ /** \brief XML-Tag "hotspotRadiusInMM": radius of hotspot */
+ double m_HotspotRadiusInMM;
+
+ // XML-Tag
+
+ /** \brief XML-Tag "maximumSizeX": maximum position of ROI in x-dimension */
+ vnl_vector m_MaxIndexX;
+ /** \brief XML-Tag "minimumSizeX": minimum position of ROI in x-dimension */
+ vnl_vector m_MinIndexX;
+ /** \brief XML-Tag "maximumSizeX": maximum position of ROI in y-dimension */
+ vnl_vector m_MaxIndexY;
+ /** \brief XML-Tag "minimumSizeX": minimum position of ROI in y-dimension */
+ vnl_vector m_MinIndexY;
+ /** \brief XML-Tag "maximumSizeX": maximum position of ROI in z-dimension */
+ vnl_vector m_MaxIndexZ;
+ /** \brief XML-Tag "minimumSizeX": minimum position of ROI in z-dimension */
+ vnl_vector m_MinIndexZ;
+
+ /** \brief XML-Tag "label": value of label */
+ vnl_vector m_Label;
+
+ //XML-Tag
+
+ /** \brief XML-Tag "minimum": minimum inside hotspot */
+ vnl_vector m_HotspotMin;
+ /** \brief XML-Tag "maximum": maximum inside hotspot */
+ vnl_vector m_HotspotMax;
+ /** \brief XML-Tag "mean": mean value of hotspot */
+ vnl_vector m_HotspotMean;
+
+ /** \brief XML-Tag "maximumIndexX": x-coordinate of maximum-location inside hotspot */
+ vnl_vector m_HotspotMaxIndexX;
+ /** \brief XML-Tag "maximumIndexX": y-coordinate of maximum-location inside hotspot */
+ vnl_vector m_HotspotMaxIndexY;
+ /** \brief XML-Tag "maximumIndexX": z-coordinate of maximum-location inside hotspot */
+ vnl_vector m_HotspotMaxIndexZ;
+
+ /** \brief XML-Tag "maximumIndexX": x-coordinate of maximum-location inside hotspot */
+ vnl_vector m_HotspotMinIndexX;
+ /** \brief XML-Tag "maximumIndexX": y-coordinate of maximum-location inside hotspot */
+ vnl_vector m_HotspotMinIndexY;
+ /** \brief XML-Tag "maximumIndexX": z-coordinate of maximum-location inside hotspot */
+ vnl_vector m_HotspotMinIndexZ;
+
+ /** \brief XML-Tag "maximumIndexX": x-coordinate of hotspot-location */
+ vnl_vector m_HotspotIndexX;
+ /** \brief XML-Tag "maximumIndexX": y-coordinate of hotspot-location */
+ vnl_vector m_HotspotIndexY;
+ /** \brief XML-Tag "maximumIndexX": z-coordinate of hotspot-location */
+ vnl_vector m_HotspotIndexZ;
+ };
+
+ /**
+ \brief Find/Convert integer attribute in itk::DOMNode.
+ */
+ static int GetIntegerAttribute(itk::DOMNode* domNode, const std::string& tag)
+ {
+ assert(domNode);
+ MITK_TEST_CONDITION_REQUIRED( domNode->HasAttribute(tag), "Tag '" << tag << "' is defined in test parameters" );
+ std::string attributeValue = domNode->GetAttribute(tag);
+
+ int resultValue;
+ try
+ {
+ //MITK_TEST_OUTPUT( << "Converting tag value '" << attributeValue << "' for tag '" << tag << "' to integer");
+ std::stringstream(attributeValue) >> resultValue;
+ return resultValue;
+ }
+ catch(std::exception& /*e*/)
+ {
+ MITK_TEST_CONDITION_REQUIRED(false, "Convert tag value '" << attributeValue << "' for tag '" << tag << "' to integer");
+ return 0; // just to satisfy compiler
+ }
+ }
+ /**
+ \brief Find/Convert double attribute in itk::DOMNode.
+ */
+ static double GetDoubleAttribute(itk::DOMNode* domNode, const std::string& tag)
+ {
+ assert(domNode);
+ MITK_TEST_CONDITION_REQUIRED( domNode->HasAttribute(tag), "Tag '" << tag << "' is defined in test parameters" );
+ std::string attributeValue = domNode->GetAttribute(tag);
+
+ double resultValue;
+ try
+ {
+ //MITK_TEST_OUTPUT( << "Converting tag value '" << attributeValue << "' for tag '" << tag << "' to double");
+ std::stringstream(attributeValue) >> resultValue;
+ return resultValue;
+ }
+ catch(std::exception& /*e*/)
+ {
+ MITK_TEST_CONDITION_REQUIRED(false, "Convert tag value '" << attributeValue << "' for tag '" << tag << "' to double");
+ return 0.0; // just to satisfy compiler
+ }
+ }
+
+ /**
+ \brief Read XML file describing the test parameters.
+
+ Reads XML file given in first commandline parameter in order
+ to construct a Parameters structure. The XML file should be
+ structurs as the following example, i.e. we describe the
+ three test aspects of Parameters in four different tags,
+ with all the details described as tag attributes. */
+
+ /**
+ \verbatim
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ \endverbatim
+ */
+ static Parameters ParseParameters(int argc, char* argv[])
+ {
+ MITK_TEST_CONDITION_REQUIRED(argc == 2, "Test is invoked with exactly 1 parameter (XML parameters file)");
+ MITK_INFO << "Reading parameters from file '" << argv[1] << "'";
+ std::string filename = argv[1];
+
+ Parameters result;
+
+ itk::DOMNodeXMLReader::Pointer xmlReader = itk::DOMNodeXMLReader::New();
+ xmlReader->SetFileName( filename );
+ try
+ {
+ xmlReader->Update();
+ itk::DOMNode::Pointer domRoot = xmlReader->GetOutput();
+ typedef std::vector NodeList;
+ NodeList testimages;
+ domRoot->GetChildren("testimage", testimages);
+ MITK_TEST_CONDITION_REQUIRED( testimages.size() == 1, "One test image defined" )
+ itk::DOMNode* testimage = testimages[0];
+
+ result.m_ImageRows = GetIntegerAttribute( testimage, "image-rows" );
+ result.m_ImageColumns = GetIntegerAttribute( testimage, "image-columns" );
+ result.m_ImageSlices = GetIntegerAttribute( testimage, "image-slices" );
+
+ result.m_NumberOfGaussian = GetIntegerAttribute( testimage, "numberOfGaussians" );
+
+ result.m_Spacing[0] = GetDoubleAttribute(testimage, "spacingX");
+ result.m_Spacing[1] = GetDoubleAttribute(testimage, "spacingY");
+ result.m_Spacing[2] = GetDoubleAttribute(testimage, "spacingZ");
+
+ result.m_EntireHotspotInImage = GetIntegerAttribute( testimage, "entireHotSpotInImage" );
+
+ MITK_TEST_OUTPUT( << "Read size parameters (x,y,z): " << result.m_ImageRows << "," << result.m_ImageColumns << "," << result.m_ImageSlices);
+ MITK_TEST_OUTPUT( << "Read spacing parameters (x,y,z): " << result.m_Spacing[0] << "," << result.m_Spacing[1] << "," << result.m_Spacing[2]);
+
+ NodeList gaussians;
+ testimage->GetChildren("gaussian", gaussians);
+ MITK_TEST_CONDITION_REQUIRED( gaussians.size() >= 1, "At least one gaussian is defined" )
+
+ result.m_CenterX.resize(result.m_NumberOfGaussian);
+ result.m_CenterY.resize(result.m_NumberOfGaussian);
+ result.m_CenterZ.resize(result.m_NumberOfGaussian);
+
+ result.m_SigmaX.resize(result.m_NumberOfGaussian);
+ result.m_SigmaY.resize(result.m_NumberOfGaussian);
+ result.m_SigmaZ.resize(result.m_NumberOfGaussian);
+
+ result.m_Altitude.resize(result.m_NumberOfGaussian);
+
+
+ for(int i = 0; i < result.m_NumberOfGaussian ; ++i)
+ {
+ itk::DOMNode* gaussian = gaussians[i];
+
+ result.m_CenterX[i] = GetIntegerAttribute(gaussian, "centerIndexX");
+ result.m_CenterY[i] = GetIntegerAttribute(gaussian, "centerIndexY");
+ result.m_CenterZ[i] = GetIntegerAttribute(gaussian, "centerIndexZ");
+
+ result.m_SigmaX[i] = GetDoubleAttribute(gaussian, "deviationX");
+ result.m_SigmaY[i] = GetDoubleAttribute(gaussian, "deviationY");
+ result.m_SigmaZ[i] = GetDoubleAttribute(gaussian, "deviationZ");
+
+ result.m_Altitude[i] = GetDoubleAttribute(gaussian, "altitude");
+
+ result.m_CenterX[i] = result.m_CenterX[i] * result.m_Spacing[0];
+ result.m_CenterY[i] = result.m_CenterY[i] * result.m_Spacing[1];
+ result.m_CenterZ[i] = result.m_CenterZ[i] * result.m_Spacing[2];
+
+ result.m_SigmaX[i] = result.m_SigmaX[i] * result.m_Spacing[0];
+ result.m_SigmaY[i] = result.m_SigmaY[i] * result.m_Spacing[1];
+ result.m_SigmaZ[i] = result.m_SigmaZ[i] * result.m_Spacing[2];
+ }
+
+ NodeList segmentations;
+ domRoot->GetChildren("segmentation", segmentations);
+ MITK_TEST_CONDITION_REQUIRED( segmentations.size() == 1, "One segmentation defined");
+ itk::DOMNode* segmentation = segmentations[0];
+
+ result.m_NumberOfLabels = GetIntegerAttribute(segmentation, "numberOfLabels");
+ result.m_HotspotRadiusInMM = GetDoubleAttribute(segmentation, "hotspotRadiusInMM");
+
+
+ // read ROI parameters, fill result structure
+ NodeList rois;
+ segmentation->GetChildren("roi", rois);
+ MITK_TEST_CONDITION_REQUIRED( rois.size() >= 1, "At least one ROI defined" )
+
+ result.m_MaxIndexX.set_size(result.m_NumberOfLabels);
+ result.m_MinIndexX.set_size(result.m_NumberOfLabels);
+ result.m_MaxIndexY.set_size(result.m_NumberOfLabels);
+ result.m_MinIndexY.set_size(result.m_NumberOfLabels);
+ result.m_MaxIndexZ.set_size(result.m_NumberOfLabels);
+ result.m_MinIndexZ.set_size(result.m_NumberOfLabels);
+ result.m_Label.set_size(result.m_NumberOfLabels);
+
+ for(unsigned int i = 0; i < rois.size(); ++i)
+ {
+ result.m_MaxIndexX[i] = GetIntegerAttribute(rois[i], "maximumIndexX");
+ result.m_MinIndexX[i] = GetIntegerAttribute(rois[i], "minimumIndexX");
+
+ result.m_MaxIndexY[i] = GetIntegerAttribute(rois[i], "maximumIndexY");
+ result.m_MinIndexY[i] = GetIntegerAttribute(rois[i], "minimumIndexY");
+
+ result.m_MaxIndexZ[i] = GetIntegerAttribute(rois[i], "maximumIndexZ");
+ result.m_MinIndexZ[i] = GetIntegerAttribute(rois[i], "minimumIndexZ");
+
+ result.m_Label[i] = GetIntegerAttribute(rois[i], "label");
+ }
+
+ // read statistic parameters, fill result structure
+ NodeList statistics;
+ domRoot->GetChildren("statistic", statistics);
+ MITK_TEST_CONDITION_REQUIRED( statistics.size() >= 1 , "At least one statistic defined" )
+ MITK_TEST_CONDITION_REQUIRED( statistics.size() == rois.size(), "Same number of rois and corresponding statistics defined");
+
+ result.m_HotspotMin.set_size(statistics.size());
+ result.m_HotspotMax.set_size(statistics.size());
+ result.m_HotspotMean.set_size(statistics.size());
+
+ result.m_HotspotMinIndexX.set_size(statistics.size());
+ result.m_HotspotMinIndexY.set_size(statistics.size());
+ result.m_HotspotMinIndexZ.set_size(statistics.size());
+
+ result.m_HotspotMaxIndexX.set_size(statistics.size());
+ result.m_HotspotMaxIndexY.set_size(statistics.size());
+ result.m_HotspotMaxIndexZ.set_size(statistics.size());
+
+ result.m_HotspotIndexX.set_size(statistics.size());
+ result.m_HotspotIndexY.set_size(statistics.size());
+ result.m_HotspotIndexZ.set_size(statistics.size());
+
+ for(unsigned int i = 0; i < statistics.size(); ++i)
+ {
+ result.m_HotspotMin[i] = GetDoubleAttribute(statistics[i], "minimum");
+ result.m_HotspotMax[i] = GetDoubleAttribute(statistics[i], "maximum");
+ result.m_HotspotMean[i] = GetDoubleAttribute(statistics[i], "mean");
+
+ result.m_HotspotMinIndexX[i] = GetIntegerAttribute(statistics[i], "minimumIndexX");
+ result.m_HotspotMinIndexY[i] = GetIntegerAttribute(statistics[i], "minimumIndexY");
+ result.m_HotspotMinIndexZ[i] = GetIntegerAttribute(statistics[i], "minimumIndexZ");
+
+ result.m_HotspotMaxIndexX[i] = GetIntegerAttribute(statistics[i], "maximumIndexX");
+ result.m_HotspotMaxIndexY[i] = GetIntegerAttribute(statistics[i], "maximumIndexY");
+ result.m_HotspotMaxIndexZ[i] = GetIntegerAttribute(statistics[i], "maximumIndexZ");
+
+ result.m_HotspotIndexX[i] = GetIntegerAttribute(statistics[i], "hotspotIndexX");
+ result.m_HotspotIndexY[i] = GetIntegerAttribute(statistics[i], "hotspotIndexY");
+ result.m_HotspotIndexZ[i] = GetIntegerAttribute(statistics[i], "hotspotIndexZ");
+ }
+ }
+ catch (std::exception& e)
+ {
+ MITK_TEST_CONDITION_REQUIRED(false, "Reading test parameters from XML file. Error message: " << e.what());
+ }
+
+ return result;
+ }
+
+ /**
+ \brief Generate an image that contains a couple of 3D gaussian distributions.
+
+ Uses the given parameters to produce a test image using class MultiGaussianImageSource.
+ */
+
+ static mitk::Image::Pointer BuildTestImage(const Parameters& testParameters)
+ {
+ mitk::Image::Pointer result;
+
+ typedef double PixelType;
+ const unsigned int Dimension = 3;
+ typedef itk::Image ImageType;
+ ImageType::Pointer image = ImageType::New();
+ typedef itk::MultiGaussianImageSource< ImageType > MultiGaussianImageSource;
+ MultiGaussianImageSource::Pointer gaussianGenerator = MultiGaussianImageSource::New();
+ ImageType::SizeValueType size[3];
+ size[0] = testParameters.m_ImageColumns;
+ size[1] = testParameters.m_ImageRows;
+ size[2] = testParameters.m_ImageSlices;
+
+ itk::MultiGaussianImageSource::VectorType centerXVec, centerYVec, centerZVec, sigmaXVec, sigmaYVec, sigmaZVec, altitudeVec;
+
+ for(int i = 0; i < testParameters.m_NumberOfGaussian; ++i)
+ {
+ centerXVec.push_back(testParameters.m_CenterX[i]);
+ centerYVec.push_back(testParameters.m_CenterY[i]);
+ centerZVec.push_back(testParameters.m_CenterZ[i]);
+
+ sigmaXVec.push_back(testParameters.m_SigmaX[i]);
+ sigmaYVec.push_back(testParameters.m_SigmaY[i]);
+ sigmaZVec.push_back(testParameters.m_SigmaZ[i]);
+
+ altitudeVec.push_back(testParameters.m_Altitude[i]);
+ }
+
+ ImageType::SpacingType spacing;
+
+ for(unsigned int i = 0; i < Dimension; ++i)
+ spacing[i] = testParameters.m_Spacing[i];
+
+ gaussianGenerator->SetSize( size );
+ gaussianGenerator->SetSpacing( spacing );
+ gaussianGenerator->SetRadius(testParameters.m_HotspotRadiusInMM);
+ gaussianGenerator->SetNumberOfGausssians(testParameters.m_NumberOfGaussian);
+
+ gaussianGenerator->AddGaussian(centerXVec, centerYVec, centerZVec,
+ sigmaXVec, sigmaYVec, sigmaZVec, altitudeVec);
+
+ gaussianGenerator->Update();
+
+ image = gaussianGenerator->GetOutput();
+
+ mitk::CastToMitkImage(image, result);
+
+ return result;
+ }
+
+ /**
+ \brief Calculates hotspot statistics for given test image and ROI parameters.
+
+ Uses ImageStatisticsCalculator to find a hotspot in a defined ROI within the given image.
+ */
+ static mitk::ImageStatisticsCalculator::Statistics CalculateStatistics(mitk::Image* image, const Parameters& testParameters, unsigned int label)
+ {
+ mitk::ImageStatisticsCalculator::Statistics result;
+ const unsigned int Dimension = 3;
+ typedef itk::Image MaskImageType;
+ MaskImageType::Pointer mask = MaskImageType::New();
+
+ MaskImageType::SizeType size;
+ MaskImageType::SpacingType spacing;
+ MaskImageType::IndexType start;
+
+ mitk::ImageStatisticsCalculator::Pointer statisticsCalculator = mitk::ImageStatisticsCalculator::New();
+ statisticsCalculator->SetImage(image);
+ mitk::Image::Pointer mitkMaskImage;
+
+ if((testParameters.m_MaxIndexX[label] > testParameters.m_MinIndexX[label] && testParameters.m_MinIndexX[label] >= 0) &&
+ (testParameters.m_MaxIndexY[label] > testParameters.m_MinIndexY[label] && testParameters.m_MinIndexY[label] >= 0) &&
+ (testParameters.m_MaxIndexZ[label] > testParameters.m_MinIndexZ[label] && testParameters.m_MinIndexZ[label] >= 0))
+ {
+ for(unsigned int i = 0; i < Dimension; ++i)
+ {
+ start[i] = 0;
+ spacing[i] = testParameters.m_Spacing[i];
+ }
+
+ size[0] = testParameters.m_ImageColumns;
+ size[1] = testParameters.m_ImageRows;
+ size[2] = testParameters.m_ImageSlices;
+
+ MaskImageType::RegionType region;
+ region.SetIndex(start);
+ region.SetSize(size);
+
+ mask->SetSpacing(spacing);
+ mask->SetRegions(region);
+ mask->Allocate();
+
+ typedef itk::ImageRegionIteratorWithIndex MaskImageIteratorType;
+ MaskImageIteratorType maskIt(mask, region);
+
+ for(maskIt.GoToBegin(); !maskIt.IsAtEnd(); ++maskIt)
+ {
+ maskIt.Set(0);
+ }
+
+ for(unsigned int i = 0; i < testParameters.m_NumberOfLabels; ++i)
+ {
+
+ for(maskIt.GoToBegin(); !maskIt.IsAtEnd(); ++maskIt)
+ {
+ MaskImageType::IndexType index = maskIt.GetIndex();
+
+ if((index[0] >= testParameters.m_MinIndexX[i] && index[0] <= testParameters.m_MaxIndexX[i] ) &&
+ (index[1] >= testParameters.m_MinIndexY[i] && index[1] <= testParameters.m_MaxIndexY[i] ) &&
+ (index[2] >= testParameters.m_MinIndexZ[i] && index[2] <= testParameters.m_MaxIndexZ[i] ))
+ {
+ maskIt.Set(testParameters.m_Label[i]);
+ }
+ }
+ }
+
+ MITK_DEBUG << "Masking mode has set to image";
+ mitk::CastToMitkImage(mask, mitkMaskImage);
+ statisticsCalculator->SetImageMask(mitkMaskImage);
+ statisticsCalculator->SetMaskingModeToImage();
+ }
+ else
+ {
+ MITK_DEBUG << "Masking mode has set to none";
+ statisticsCalculator->SetMaskingModeToNone();
+ }
+
+ statisticsCalculator->SetHotspotRadiusInMM(testParameters.m_HotspotRadiusInMM);
+ statisticsCalculator->SetCalculateHotspot(true);
+
+ if(testParameters.m_EntireHotspotInImage == 1)
+ {
+ MITK_INFO << "Hotspot must be completly inside image";
+ statisticsCalculator->SetHotspotMustBeCompletlyInsideImage(true);
+ }
+ else
+ {
+ MITK_INFO << "Hotspot must not be completly inside image";
+ statisticsCalculator->SetHotspotMustBeCompletlyInsideImage(false);
+ }
+
+ statisticsCalculator->ComputeStatistics();
+ result = statisticsCalculator->GetStatistics(0, label);
+
+ return result;
+ }
+
+ static void ValidateStatisticsItem(const std::string& label, double testvalue, double reference, double tolerance)
+ {
+ double diff = ::fabs(reference - testvalue);
+ MITK_TEST_CONDITION( diff < tolerance, "'" << label << "' value close enough to reference value "
+ "(value=" << testvalue <<
+ ", reference=" << reference <<
+ ", diff=" << diff << ")" );
+ }
+
+ static void ValidateStatisticsItem(const std::string& label, const vnl_vector& testvalue, const vnl_vector& reference)
+ {
+ double diffX = ::fabs(double(testvalue[0] - reference[0]));
+ double diffY = ::fabs(double(testvalue[1] - reference[1]));
+ double diffZ = ::fabs(double(testvalue[2] - reference[2]));
+
+ std::stringstream testPosition;
+ testPosition << testvalue[0] << "," << testvalue[1] << "," << testvalue[2];
+ std::stringstream referencePosition;
+ referencePosition << reference[0] << "," << reference[1] << "," << reference[2];
+ MITK_TEST_CONDITION( diffX < mitk::eps && diffY < mitk::eps && diffZ < mitk::eps,
+ "'" << label << "' close enough to reference value " <<
+ "(value=[" << testPosition.str() << "]," <<
+ " reference=[" << referencePosition.str() << "]");
+ }
+
+
+ /**
+ \brief Compares calculated against actual statistics values.
+
+ Checks validness of all statistics aspects. Lets test fail if any aspect is not sufficiently equal.
+ */
+ static void ValidateStatistics(const mitk::ImageStatisticsCalculator::Statistics& statistics, const Parameters& testParameters, unsigned int label)
+ {
+ // check all expected test result against actual results
+ double eps = 0.25; // value above the largest tested difference
+
+ ValidateStatisticsItem("Hotspot mean", statistics.GetHotspotStatistics().GetMean(), testParameters.m_HotspotMean[label], eps);
+ ValidateStatisticsItem("Hotspot maximum", statistics.GetHotspotStatistics().GetMax(), testParameters.m_HotspotMax[label], eps);
+ ValidateStatisticsItem("Hotspot minimum", statistics.GetHotspotStatistics().GetMin(), testParameters.m_HotspotMin[label], eps);
+
+ vnl_vector referenceHotspotCenterIndex; referenceHotspotCenterIndex.set_size(3);
+ referenceHotspotCenterIndex[0] = testParameters.m_HotspotIndexX[label];
+ referenceHotspotCenterIndex[1] = testParameters.m_HotspotIndexY[label];
+ referenceHotspotCenterIndex[2] = testParameters.m_HotspotIndexZ[label];
+ ValidateStatisticsItem("Hotspot center position", statistics.GetHotspotStatistics().GetHotspotIndex(), referenceHotspotCenterIndex);
+
+ // TODO we do not test minimum/maximum positions within the peak/hotspot region, because
+ // these positions are not unique, i.e. there are multiple valid minima/maxima positions.
+ // One solution would be to modify the test cases in order to achive clear positions.
+ // The BETTER/CORRECT solution would be to change the singular position into a set of positions / a region
+ }
+};
+/**
+ \brief Verifies that hotspot statistics part of ImageStatisticsCalculator.
+
+ The test reads parameters from an XML-file to generate a test-image, calculates the hotspot statistics of the image
+ and checks if the calculated statistics are the same as the specified values of the XML-file.
+*/
+int mitkImageStatisticsHotspotTest(int argc, char* argv[])
+{
+ MITK_TEST_BEGIN("mitkImageStatisticsHotspotTest")
+ try {
+ mitkImageStatisticsHotspotTestClass::Parameters parameters = mitkImageStatisticsHotspotTestClass::ParseParameters(argc,argv);
+
+ mitk::Image::Pointer image = mitkImageStatisticsHotspotTestClass::BuildTestImage(parameters);
+ MITK_TEST_CONDITION_REQUIRED( image.IsNotNull(), "Generate test image" );
+
+ for(unsigned int label = 0; label < parameters.m_NumberOfLabels; ++label)
+ {
+ mitk::ImageStatisticsCalculator::Statistics statistics = mitkImageStatisticsHotspotTestClass::CalculateStatistics(image, parameters, label);
+
+ mitkImageStatisticsHotspotTestClass::ValidateStatistics(statistics, parameters, label);
+ std::cout << std::endl;
+ }
+
+
+ }
+ catch (std::exception& e)
+ {
+ std::cout << "Error: " << e.what() << std::endl;
+ MITK_TEST_CONDITION_REQUIRED( false, "Exception occurred during test execution: " << e.what() );
+ }
+ catch(...)
+ {
+ MITK_TEST_CONDITION_REQUIRED( false, "Exception occurred during test execution." );
+ }
+
+
+ MITK_TEST_END()
+}
diff --git a/Modules/ImageStatistics/Testing/mitkMultiGaussianTest.cpp b/Modules/ImageStatistics/Testing/mitkMultiGaussianTest.cpp
new file mode 100644
index 0000000000..3f70bc9d9d
--- /dev/null
+++ b/Modules/ImageStatistics/Testing/mitkMultiGaussianTest.cpp
@@ -0,0 +1,546 @@
+/*===================================================================
+
+The Medical Imaging Interaction Toolkit (MITK)
+
+Copyright (c) German Cancer Research Center,
+Division of Medical and Biological Informatics.
+All rights reserved.
+
+This software is distributed WITHOUT ANY WARRANTY; without
+even the implied warranty of MERCHANTABILITY or FITNESS FOR
+A PARTICULAR PURPOSE.
+
+See LICENSE.txt or http://www.mitk.org for details.
+
+===================================================================*/
+
+#include "mitkTestingMacros.h"
+#include "itkMultiGaussianImageSource.h"
+#include
+#include
+#include
+#include
+#include
+#include
+#include
+#include
+
+// Commandline:(for exmaple) mitkMultiGaussianTest C:/temp/output C:/temp/inputFile.xml
+//
+//For Example: inputFile.xml
+//
+//
+//
+//
+//
+//
+//
+//
+//
+//
+//For Example: output.xml
+//
+//
+//
+//
+//
+//
+//
+//
+//
+//
+
+
+bool IsInOtherROI(int,
+ itk::MultiGaussianImageSource >::VectorType,
+ itk::MultiGaussianImageSource >::VectorType,
+ itk::MultiGaussianImageSource >::VectorType,
+ itk::MultiGaussianImageSource >::VectorType,
+ itk::MultiGaussianImageSource >::VectorType,
+ itk::MultiGaussianImageSource >::VectorType);
+
+
+int mitkMultiGaussianTest(int argc, char* argv[])
+{
+ // Read the parmaeter from a .xml File.
+ // In the inputFile.xml we find the characteristics of the Gaussian and the ROI's. Hier we can have more then one ROI -> we find the hot spot for each of the ROI's; we can set the entire HotSpot to be in the image or just its midpoint, but not necessary the whole HotSpot.
+
+ const unsigned int Dimension = 3;
+ typedef double PixelType;
+ typedef itk::DOMNode::Pointer DOMNodeType;
+ typedef itk::Image ImageType;
+ typedef itk::MultiGaussianImageSource< ImageType > MultiGaussianImageSource;
+ std::string outputFilename = argv[1], name;
+ int numberOfImages;
+ double centerX, centerY, centerZ, sigmaX, sigmaY, sigmaZ, altitude, hotSpotRadiusInMM;
+ unsigned int numberOfGaussians, minWidthOfGaussian, maxWidthOfGaussian, minAltitudeOfGaussian, maxAltitudeOfGaussian, numberOfLabels;
+ itk::MultiGaussianImageSource< ImageType >::VectorType centerXVec, centerYVec, centerZVec, sigmaXVec, sigmaYVec, sigmaZVec, altitudeVec, ROImaxIndexX, ROIminIndexX, ROImaxIndexY, ROIminIndexY, ROImaxIndexZ, ROIminIndexZ, label;
+ itk::MultiGaussianImageSource< ImageType >::ItkVectorType regionOfInterestMax, regionOfInterestMin;
+ itk::MultiGaussianImageSource< ImageType >::IndexType sphereMidpt, maxValueIndexInSphere, minValueIndexInSphere;
+ MultiGaussianImageSource::Pointer gaussianGenerator;
+ itk::DOMNodeXMLWriter::Pointer xmlWriter;
+ itk::MultiGaussianImageSource< ImageType >::SpacingValueArrayType spacing;
+ DOMNodeType domTestCase, domTestImage, domGaussian, domSegmentation, domStatistics, domROI;
+ ImageType::SizeValueType size[3];
+ std::stringstream ss;
+ double radius = pow(itk::Math::one_over_pi * 0.75 , 1.0 / 3.0) * 10;
+ char * fileNamePointer;
+ std::string attributeValue;
+ double value;
+ bool entireHotSpotInImage;
+ int maxIndex, minIndex;
+
+ std::string filename = argv[2];
+ itk::DOMNodeXMLReader::Pointer xmlReader = itk::DOMNodeXMLReader::New();
+ xmlReader->SetFileName( filename );
+ xmlReader->Update();
+ itk::DOMNode::Pointer domRoot = xmlReader->GetOutput();
+ typedef std::vector NodeList;
+
+ // read test image parameters, fill result structure
+ NodeList testimages;
+ domRoot->GetChildren("testimage", testimages);
+ MITK_TEST_CONDITION_REQUIRED( testimages.size() == 1, "One test image defined" )
+ itk::DOMNode* testimage = testimages[0];
+
+ attributeValue = testimage->GetAttribute("image-rows");
+ std::stringstream(attributeValue) >> size[0];
+ attributeValue = testimage->GetAttribute("image-columns");
+ std::stringstream(attributeValue) >> size[1];
+ attributeValue = testimage->GetAttribute("image-slices");
+ std::stringstream(attributeValue) >> size[2];
+
+ attributeValue = testimage->GetAttribute( "numberOfGaussians" );
+ std::stringstream(attributeValue) >> numberOfGaussians;
+
+ attributeValue = testimage->GetAttribute( "spacingX" );
+ std::stringstream(attributeValue) >> spacing[0];
+ attributeValue = testimage->GetAttribute( "spacingY" );
+ std::stringstream(attributeValue) >> spacing[1];
+ attributeValue = testimage->GetAttribute( "spacingZ" );
+ std::stringstream(attributeValue) >> spacing[2];
+ attributeValue = testimage->GetAttribute( "entireHotSpotInImage" );
+ std::stringstream(attributeValue) >> entireHotSpotInImage;
+
+ std::cout << "Read size parameters (x,y,z): " << size[0] << ", " << size[1] << ", " << size[2] << "\n" << std::endl;
+ std::cout << "Read spacing parameters (x,y,z): " << spacing[0] << ", " << spacing[1] << ", " << spacing[2]<< "\n" << std::endl;
+
+ NodeList gaussians;
+ testimage->GetChildren("gaussian", gaussians);
+ itk::DOMNode* gaussian;
+ for(int i = 0; i < numberOfGaussians ; ++i)
+ {
+ gaussian = gaussians[i];
+ //TODO
+ attributeValue = gaussian->GetAttribute( "centerIndexX" );
+ std::stringstream(attributeValue) >> value;
+ centerXVec.push_back(value * spacing[0]);
+
+ attributeValue = gaussian->GetAttribute( "centerIndexY" );
+ std::stringstream(attributeValue) >> value;
+ centerYVec.push_back(value * spacing[1]);
+
+ attributeValue = gaussian->GetAttribute( "centerIndexZ" );
+ std::stringstream(attributeValue) >> value;
+ centerZVec.push_back(value * spacing[2]);
+
+ std::cout << "Read center of Gaussian (x,y,z) in mm: " << centerXVec[i] << ", " << centerYVec[i] << ", " << centerZVec[i] << "\n" << std::endl;
+
+ attributeValue = gaussian->GetAttribute( "deviationX" );
+ std::stringstream(attributeValue) >> value;
+ sigmaXVec.push_back(value * spacing[0]);
+
+ attributeValue = gaussian->GetAttribute( "deviationY" );
+ std::stringstream(attributeValue) >> value;
+ sigmaYVec.push_back(value * spacing[1]);
+
+ attributeValue = gaussian->GetAttribute( "deviationZ" );
+ std::stringstream(attributeValue) >> value;
+ sigmaZVec.push_back(value * spacing[2]);
+
+ std::cout << "Read deviation of Gaussian (x,y,z) in mm: " << sigmaXVec[i] << ", " << sigmaYVec[i] << ", " << sigmaZVec[i] << "\n" << std::endl;
+
+ attributeValue = gaussian->GetAttribute( "altitude" );
+ std::stringstream(attributeValue) >> value;
+ altitudeVec.push_back(value);
+ std::cout << "Read altitude: " << altitudeVec[i] << "\n" << std::endl;
+ }
+
+ // read ROI's parameter
+ NodeList segmentations;
+ domRoot->GetChildren("segmentation", segmentations);
+ MITK_TEST_CONDITION_REQUIRED( segmentations.size() == 1, "One ROI image defined" )
+ itk::DOMNode* segmentation = segmentations[0];
+
+ attributeValue = segmentation->GetAttribute("numberOfLabels");
+ std::stringstream(attributeValue) >> numberOfLabels;
+ attributeValue = segmentation->GetAttribute("hotspotRadiusInMM");
+ std::stringstream(attributeValue) >> hotSpotRadiusInMM;
+
+ std::cout << "Read number of labels: " << numberOfLabels << std::endl;
+ std::cout << "Read radius in mm : " << hotSpotRadiusInMM << std::endl;
+
+ NodeList rois;
+ segmentation->GetChildren("roi", rois);
+ itk::DOMNode* roi;
+ // for each label i take the ROI and set it to be the i'th element of ROImaxIndex* and ROIminIndex* ( * = X, Y, Z)
+ for(int i = 0; i < numberOfLabels ; ++i)
+ {
+ roi = rois[i];
+
+ attributeValue = roi->GetAttribute( "label" );
+ std::stringstream(attributeValue) >> value;
+ label.push_back(value);
+
+ attributeValue = roi->GetAttribute( "maximumIndexX" );
+ std::stringstream(attributeValue) >> value;
+ ROImaxIndexX.push_back(value);
+
+ attributeValue = roi->GetAttribute( "minimumIndexX" );
+ std::stringstream(attributeValue) >> value;
+ ROIminIndexX.push_back(value);
+
+ attributeValue = roi->GetAttribute( "maximumIndexY" );
+ std::stringstream(attributeValue) >> value;
+ ROImaxIndexY.push_back(value);
+
+ attributeValue = roi->GetAttribute( "minimumIndexY" );
+ std::stringstream(attributeValue) >> value;
+ ROIminIndexY.push_back(value);
+
+ attributeValue = roi->GetAttribute( "maximumIndexZ" );
+ std::stringstream(attributeValue) >> value;
+ ROImaxIndexZ.push_back(value);
+
+ attributeValue = roi->GetAttribute( "minimumIndexZ" );
+ std::stringstream(attributeValue) >> value;
+ ROIminIndexZ.push_back(value);
+
+ std::cout << "Read ROI with label number: " << label[i] << " with min and max values in the x-, y-, z-Achse: [" << ROIminIndexX[i] << " " << ROImaxIndexX[i] <<"], [" << ROIminIndexY[i] << " " << ROImaxIndexY[i] <<"], [" << ROIminIndexZ[i] << " " << ROImaxIndexZ[i] <<"]\n" << std::endl;
+ }
+
+ // Check whether the ROI's are correct defined, i.e. whether the ROI's are disjoint
+ for(int i = 1; i < numberOfLabels ; ++i)
+ {
+ // check whether the edges of the i'th ROI is in another ROI included (when yes -> ERROR)
+ bool isInOtherROI = IsInOtherROI( i, ROIminIndexX, ROImaxIndexX, ROIminIndexY, ROImaxIndexY, ROIminIndexZ, ROImaxIndexZ );
+ if( isInOtherROI)
+ {
+ std::cout << "The ROI's in the different labels should be disjoint! Please define it correct. " << std::endl;
+ return 0;
+ }
+ }
+
+
+ //write test image parameter
+ xmlWriter = itk::DOMNodeXMLWriter::New();
+ domTestCase = itk::DOMNode::New();
+ domTestCase->SetName("testcase");
+ domTestImage = itk::DOMNode::New();
+ domTestImage->SetName("testimage");
+ ss.str("");
+ ss << size[0];
+ domTestImage->SetAttribute("image-rows", ss.str());
+ ss.str("");
+ ss << size[1];
+ domTestImage->SetAttribute("image-columns", ss.str());
+ ss.str("");
+ ss << size[2];
+ domTestImage->SetAttribute("image-slices", ss.str());
+ ss.str("");
+ ss << numberOfGaussians;
+ domTestImage->SetAttribute("numberOfGaussians", ss.str());
+ ss.str("");
+ ss << spacing[0];
+ domTestImage->SetAttribute("spacingX", ss.str());
+ ss.str("");
+ ss << spacing[1];
+ domTestImage->SetAttribute("spacingY", ss.str());
+ ss.str("");
+ ss << spacing[2];
+ domTestImage->SetAttribute("spacingZ", ss.str());
+ ss.str("");
+ ss << entireHotSpotInImage;
+ domTestImage->SetAttribute("entireHotSpotInImage", ss.str());
+ domTestCase->AddChildAtBegin(domTestImage);
+
+ for( unsigned int i = 0; i < numberOfGaussians; ++i)
+ {
+
+ domGaussian = itk::DOMNode::New() ;
+ domGaussian->SetName("gaussian");
+ domTestImage->AddChildAtEnd(domGaussian);
+ // write the midpoint and the daviation in pixel units
+ centerX = centerXVec[i] / spacing[0];
+ ss.str("");
+ ss << centerX; // * spacing[0]; //static_cast( static_cast( centerX / spacing[0] + 0.9999 ) );
+ domGaussian->SetAttribute("centerIndexX", ss.str());
+
+ centerY = centerYVec[i] / spacing[1];
+ ss.str("");
+ ss << centerY; // * spacing[1]; //static_cast( static_cast( centerY / spacing[1] + 0.9999 ) );
+ domGaussian->SetAttribute("centerIndexY", ss.str());
+
+ centerZ = centerZVec[i] / spacing[2];
+ ss.str("");
+ ss << centerZ; // * spacing[2]; //static_cast( static_cast( centerZ / spacing[2] + 0.9999 ) );
+ domGaussian->SetAttribute("centerIndexZ", ss.str());
+
+ sigmaX = sigmaXVec[i] / spacing[0];
+ ss.str("");
+ ss << sigmaX; // * spacing[0]; // static_cast( static_cast( sigmaX / spacing[0] + 0.9999 ) );
+ domGaussian->SetAttribute("deviationX", ss.str());
+
+ sigmaY = sigmaYVec[i] / spacing[1];
+ ss.str("");
+ ss << sigmaY; // * spacing[1]; //static_cast( static_cast( sigmaY / spacing[1] + 0.9999 ) );
+ domGaussian->SetAttribute("deviationY", ss.str());
+
+ sigmaZ = sigmaZVec[i] / spacing[2];
+ ss.str("");
+ ss << sigmaZ; // * spacing[2]; //static_cast( static_cast( sigmaZ / spacing[2] + 0.9999 ) );
+ domGaussian->SetAttribute("deviationZ", ss.str());
+
+ altitude = altitudeVec[i];
+ ss.str("");
+ ss << altitude;
+ domGaussian->SetAttribute("altitude", ss.str());
+
+ }
+
+ radius = hotSpotRadiusInMM;
+ // set the parameter for the gaussianGenerator
+ gaussianGenerator = MultiGaussianImageSource::New();
+ gaussianGenerator->SetSize( size );
+ gaussianGenerator->SetSpacing( spacing );
+ gaussianGenerator->SetRadius(radius);
+ gaussianGenerator->SetNumberOfGausssians(numberOfGaussians);
+ gaussianGenerator->AddGaussian(centerXVec, centerYVec, centerZVec, sigmaXVec, sigmaYVec, sigmaZVec, altitudeVec);
+
+ domSegmentation = itk::DOMNode::New();
+ domSegmentation->SetName("segmentation");
+ domTestCase->AddChildAtEnd(domSegmentation);
+
+ ss.str("");
+ ss << numberOfLabels;
+ domSegmentation->SetAttribute("numberOfLabels", ss.str());
+ ss.str("");
+ ss << hotSpotRadiusInMM;
+ domSegmentation->SetAttribute("hotspotRadiusInMM", ss.str());
+
+
+ // set the region of interest for each label i
+ for (unsigned int i = 0; i < numberOfLabels; ++i)
+ {
+ // Set region of interest in index values. The entire HotSpot is in the image.
+ if(entireHotSpotInImage)
+ {
+
+ // x axis region of interest------------------------------------------------------
+ minIndex = 0.0 + static_cast((radius)/spacing[0]+ 0.5);
+ maxIndex = size[0]-1-minIndex;
+ if( minIndex >= maxIndex )
+ {
+ std::cout << "The sphere is larger then the image in the x axis!" << std::endl;
+
+ }
+ // the maximum in the x-Axis
+ regionOfInterestMax.SetElement( 0, ( ROImaxIndexX[i] < maxIndex ) ? ROImaxIndexX[i] : maxIndex );
+ // the minimum in the x-Axis
+ regionOfInterestMin.SetElement( 0, ( ROIminIndexX[i] > minIndex ) ? ROIminIndexX[i] : minIndex );
+
+ // y axis region of interest------------------------------------------------------
+ minIndex = 0.0 + static_cast((radius)/spacing[1]+ 0.5);
+ maxIndex = size[1]-1-minIndex;
+ if( minIndex >= maxIndex )
+ {
+ std::cout << "The sphere is larger then the image in the y axis!" << std::endl;
+ }
+ // the maximum in the y-Axis
+ regionOfInterestMax.SetElement( 1, ( ROImaxIndexY[i] < maxIndex ) ? ROImaxIndexY[i] : maxIndex );
+ // the minimum in the y-Axis
+ regionOfInterestMin.SetElement( 1, ( ROIminIndexY[i] > minIndex ) ? ROIminIndexY[i] : minIndex );
+
+ // z axis region of interest------------------------------------------------------
+ minIndex = 0.0 + static_cast((radius)/spacing[2]+ 0.5); // int(6.2/3.0 + 0.5) = 2
+ maxIndex = size[2]-1-minIndex;
+ if( minIndex >= maxIndex )
+ {
+ std::cout << "The sphere is larger then the image in the z axis!" << std::endl;
+ }
+ // the maximum in the z-Axis
+ regionOfInterestMax.SetElement( 2, ( ROImaxIndexZ[i] < maxIndex ) ? ROImaxIndexZ[i] : maxIndex );
+ // the minimum in the z-Axis
+ regionOfInterestMin.SetElement( 2, ( ROIminIndexZ[i] > minIndex ) ? ROIminIndexZ[i] : minIndex );
+
+ }
+ // Set region of interest in index values. The midpoint of the HotSpot is in the image, but not necessary the whole HotSpot
+ else
+ {
+ // x axis region of interest------------------------------------------------------
+ regionOfInterestMax.SetElement( 0, ROImaxIndexX[i] );
+ regionOfInterestMin.SetElement( 0, ROIminIndexX[i] );
+ // y axis region of interest------------------------------------------------------
+ regionOfInterestMax.SetElement( 1, ROImaxIndexY[i] );
+ regionOfInterestMin.SetElement( 1, ROIminIndexY[i] );
+ // z axis region of interest------------------------------------------------------
+ regionOfInterestMax.SetElement( 2, ROImaxIndexZ[i] );
+ regionOfInterestMin.SetElement( 2, ROIminIndexZ[i] );
+
+ }
+
+
+ gaussianGenerator->SetRegionOfInterest(regionOfInterestMin, regionOfInterestMax);
+ gaussianGenerator->Update();
+
+
+ //write region of interest for the .xml file
+ domROI = itk::DOMNode::New();
+ domROI->SetName("roi");
+ domSegmentation->AddChildAtEnd(domROI);
+
+ ss.str("");
+ ss << label[i];
+ domROI->SetAttribute("label", ss.str());
+ ss.str("");
+ ss << ROImaxIndexX[i];
+ domROI->SetAttribute("maximumIndexX", ss.str());
+ ss.str("");
+ ss << ROIminIndexX[i];
+ domROI->SetAttribute("minimumIndexX", ss.str());
+ ss.str("");
+ ss << ROImaxIndexY[i];
+ domROI->SetAttribute("maximumIndexY", ss.str());
+ ss.str("");
+ ss << ROIminIndexY[i];
+ domROI->SetAttribute("minimumIndexY", ss.str());
+ ss.str("");
+ ss << ROImaxIndexZ[i];
+ domROI->SetAttribute("maximumIndexZ", ss.str());
+ ss.str("");
+ ss << ROIminIndexZ[i];
+ domROI->SetAttribute("minimumIndexZ", ss.str());
+
+
+ // Calculate the mean value and the midpoint of the wanted sphere.
+ gaussianGenerator->CalculateTheMidpointAndTheMeanValueWithOctree();
+
+ //peak and peak coordinate
+ domStatistics = itk::DOMNode::New();
+ domStatistics->SetName("statistic");
+ domTestCase->AddChildAtEnd(domStatistics);
+ sphereMidpt = gaussianGenerator->GetSphereMidpoint();
+ ss.str("");
+ ss << sphereMidpt[0];
+ domStatistics->SetAttribute("hotspotIndexX", ss.str());
+ ss.str("");
+ ss << sphereMidpt[1];
+ domStatistics->SetAttribute("hotspotIndexY", ss.str());
+ ss.str("");
+ ss << sphereMidpt[2];
+ domStatistics->SetAttribute("hotspotIndexZ", ss.str());
+ ss.str("");
+ ss << gaussianGenerator->GetMaxMeanValue();
+ domStatistics->SetAttribute("mean", ss.str());
+
+
+ //maximum and maximum coordinate
+ gaussianGenerator->CalculateMaxAndMinInSphere();
+ maxValueIndexInSphere = gaussianGenerator->GetMaxValueIndexInSphere();
+ ss.str("");
+ ss << maxValueIndexInSphere[0];
+ domStatistics->SetAttribute("maximumIndexX", ss.str());
+ ss.str("");
+ ss << maxValueIndexInSphere[1];
+ domStatistics->SetAttribute("maximumIndexY", ss.str());
+ ss.str("");
+ ss << maxValueIndexInSphere[2];
+ domStatistics->SetAttribute("maximumIndexZ", ss.str());
+ ss.str("");
+ ss << gaussianGenerator->GetMaxValueInSphere();
+ domStatistics->SetAttribute("maximum", ss.str());
+
+ //minimum and minimum coordinate
+ minValueIndexInSphere = gaussianGenerator->GetMinValueIndexInSphere();
+ ss.str("");
+ ss << minValueIndexInSphere[0];
+ domStatistics->SetAttribute("minimumIndexX", ss.str());
+ ss.str("");
+ ss << minValueIndexInSphere[1];
+ domStatistics->SetAttribute("minimumIndexY", ss.str());
+ ss.str("");
+ ss << minValueIndexInSphere[2];
+ domStatistics->SetAttribute("minimumIndexZ", ss.str());
+ ss.str("");
+ ss << gaussianGenerator->GetMinValueInSphere();
+ domStatistics->SetAttribute("minimum", ss.str());
+ }
+
+ // .xml (Data)
+ ss.str("");
+ ss << outputFilename << ".xml";
+ name = ss.str();
+ fileNamePointer = (char*) name.c_str();
+ xmlWriter->SetFileName( fileNamePointer);
+ xmlWriter->SetInput( domTestCase );
+ xmlWriter->Update();
+ ImageType::Pointer gaussianImage = gaussianGenerator->GetOutput();
+
+ //.nrrd (Image)
+ typedef itk::ImageFileWriter< ImageType > WriterType;
+ WriterType::Pointer writer = WriterType::New();
+ ss.str("");
+ ss << outputFilename << ".nrrd";
+ name = ss.str();
+ fileNamePointer = (char*) name.c_str();
+ writer->SetFileName( fileNamePointer);
+ writer->SetInput( gaussianImage );
+ writer->Update();
+
+}
+
+
+
+// check whether the edges of the i'th ROI is in another ROI included
+bool IsInOtherROI(int i,
+ itk::MultiGaussianImageSource >::VectorType ROIminIndexX,
+ itk::MultiGaussianImageSource >::VectorType ROImaxIndexX,
+ itk::MultiGaussianImageSource >::VectorType ROIminIndexY,
+ itk::MultiGaussianImageSource >::VectorType ROImaxIndexY,
+ itk::MultiGaussianImageSource >::VectorType ROIminIndexZ,
+ itk::MultiGaussianImageSource >::VectorType ROImaxIndexZ )
+{
+ bool error = 0;
+ std::vector xBound, yBound, zBound;
+ xBound.push_back( ROIminIndexX[i] );
+ xBound.push_back( ROImaxIndexX[i] );
+ yBound.push_back( ROIminIndexY[i] );
+ yBound.push_back( ROImaxIndexY[i] );
+ zBound.push_back( ROIminIndexZ[i] );
+ zBound.push_back( ROImaxIndexZ[i] );
+ //for each ROI
+ for( unsigned int j = 0; j < i; ++j )
+ {
+ for( unsigned int x = 0; x < 2; ++x)
+ {
+ for( unsigned int y = 0; y < 2; ++y)
+ {
+ for( unsigned int z = 0; z < 2; ++z)
+ {
+ double edgeXCoord = xBound[x];
+ double edgeYCoord = yBound[y];
+ double edgeZCoord = zBound[z];
+ // check if the edge with coordinate [edgeXCoord; edgeYCoord; edgeZCoord] is inside the j'th ROI
+ if ( ROIminIndexX[j] < edgeXCoord && edgeXCoord < ROImaxIndexX[j] &&
+ ROIminIndexY[j] < edgeYCoord && edgeYCoord < ROImaxIndexY[j] &&
+ ROIminIndexZ[j] < edgeZCoord && edgeZCoord < ROImaxIndexZ[j])
+ {
+ error = 1;
+ return error;
+ }
+ }
+ }
+ }
+ }
+ return error;
+}
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diff --git a/Modules/ImageStatistics/itkMultiGaussianImageSource.h b/Modules/ImageStatistics/itkMultiGaussianImageSource.h
new file mode 100644
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--- /dev/null
+++ b/Modules/ImageStatistics/itkMultiGaussianImageSource.h
@@ -0,0 +1,374 @@
+/*=========================================================================
+ *
+ * Copyright Insight Software Consortium
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0.txt
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *
+ *=========================================================================*/
+/*=========================================================================
+ *
+ * Portions of this file are subject to the VTK Toolkit Version 3 copyright.
+ *
+ * Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen
+ *
+ * For complete copyright, license and disclaimer of warranty information
+ * please refer to the NOTICE file at the top of the ITK source tree.
+ *
+ *=========================================================================*/
+#ifndef __itkMultiGaussianImageSource_h
+#define __itkMultiGaussianImageSource_h
+
+#include "itkImageSource.h"
+#include "itkNumericTraits.h"
+#include "itkImageRegionIteratorWithIndex.h"
+#include "itkImageFileWriter.h"
+#include
+
+
+namespace itk
+{
+/** \class MultiGaussianImageSource
+
+\brief Generate an 3-dimensional multigaussian image.
+
+This class defines an 3-dimensional Image, in which the value at one voxel equals the value of a multigaussian function evaluated at the voxel's coordinates. The multigaussian function is built as a sum of N gaussian function and is defined by the following parameters (\ref Generation-of-a-multigauss-image):
+
+1. CenterX, CenterY, CenterZ - vectors of the size of N determining the expectancy value at the x-, y- and the z-axis. That means: The i-th gaussian bell curve takes its maximal value at the voxel with index [CenterX(i); CenterY(i); Centerz(i)].
+
+2. SigmaX, SigmaY, SigmaZ - vectors of the size of N determining the deviation at the x-, y- and the z-axis. That means: The width of the i-th gaussian bell curve is determined by the deviation in the x-axis, which is SigmaX(i), in the y-axis is SigmaY(i) and in the z-axis is SigmaZ(i).
+
+3. Altitude - vector of the size of N determining the altitude: the i-th gaussian bell curve has a height of Altitude(i).
+This class allows by the method CalculateMidpointAndMeanValue() to find a sphere with a specified radius that has a maximal mean value over all sphere with that radius with midpoint inside or on the boundary of the image. Furthermore it can calculate the maximal und minimal pixel intensities and whose indices in the founded sphere.
+
+To serve as a test tool for ImageStatisticsCalculator, esp. the "hotspot search" feature of this class, MultiGaussianImageSource is also able to calculate the position of a sphere that maximizes the mean value of the voxels within the sphere (\ref Algorithm-for-calculating-statistic-in-a-sphere).
+
+\section Generation-of-a-multigauss-image Generation of a multigauss image
+
+A multigauss function consists of the sum of \f$ N \f$ gauss function. The \f$ i \f$-th \linebreak (\f$0 \leq i \leq N \f$) gaussian is described with the following seven parameters (see above):
+- \f$ x_0^{(i)} \f$ is the expectancy value in the \f$ x \f$-Axis
+- \f$ y_0^{(i)} \f$ is the expectancy value in the \f$ y \f$-Axis
+- \f$ z_0^{(i)} \f$ is the expectancy value in the \f$ z \f$-Axis
+- \f$ \sigma_x^{(i)} \f$ is the deviation in the \f$ x \f$-Axis
+- \f$ \sigma_y^{(i)} \f$ is the deviation in the \f$ y \f$-Axis
+- \f$ \sigma_z^{(i)} \f$ is the deviation in the \f$ z \f$-Axis
+- \f$ a^{(i)} \f$ is the altitude of the gaussian.
+
+A gauss function has the following form:
+
+\f{eqnarray}{
+\nonumber
+f^{(i)}(x,y,z) = a^{(i)}
+exp \left[ - \left(
+\frac{(x - x_0^{(i)})^2}{2 (\sigma_x^{(i)})^2} +
+\frac{(y - y_0^{(i)})^2}{2 (\sigma_y^{(i)})^2} +
+\frac{(z - z_0^{(i)})^2}{2 (\sigma_z^{(i)})^2}
+\right) \right].
+\f}
+
+A multigauss function has then the form:
+
+\f{align*}{
+f_N(x,y,z) =& \sum_{i=0}^{N}f^{(i)}(x,y,z)\\
+=&\sum_{0}^{N} a^{(i)}
+exp \left[ - \left(
+\frac{(x - x_0^{(i)})^2}{2 (\sigma_x^{(i)})^2} +
+\frac{(y - y_0^{(i)})^2}{2 (\sigma_y^{(i)})^2} +
+\frac{(z - z_0^{(i)})^2}{2 (\sigma_z^{(i)})^2}
+\right) \right].
+\f}
+
+The multigauss function \f$f_N\f$ will be evaluated at each voxel coordinate to become the voxel intensity.
+
+\section Algorithm-for-calculating-statistic-in-a-sphere Algorithm for calculating statistic in a sphere
+
+This section explains how we can find a sphere region which has a maximal mean value over all sphere regions with a fixed radius. Furthermore we want to calculate the maximal and minimal value in the wanted sphere.
+
+To calculate the mean value in a sphere we integrate the gaussians over the whole sphere. The antiderivative is unknown as an explicit function, but we have a value table for the distribution function of the normal distribution \f$ \Phi(x) \f$ for \f$ x \f$ between \f$ -3.99 \f$ and \f$ 3.99 \f$ with step size \f$ 0.01 \f$. The only problem is that we cannot integrate over a spherical region, because we have an 3-dim integral and therefore are the integral limits dependent from each other and we cannot evaluate \f$ \Phi \f$. So we approximate the sphere with cuboids inside the sphere and prisms on the boundary of the sphere. We calculate these cuboids with the octree recursive method: We start by subdividing the wrapping box of the sphere in eight cuboids. Further we subdivide each cuboid in eight cuboids and check for each of them, whether it is inside or outside the sphere or whether it intersects the sphere surface. We save those of them, which are inside the sphere and continue to subdivide the cuboids that intersect the sphere until the recursion breaks. In the last step we take the half of the cuboids on the boundary and this are the prisms. Now we can calculate and sum the integrals over the cuboids and divide through the volume of the body to obtain the mean value.
+
+For each cuboid \f$ Q = [a_1, b_1]\times[a_2, b_2]\times[a_3, b_3] \f$ we apply Fubini's theorem for integrable functions and become for the integral the following:
+
+\f{align*}{
+m_k =& \sum_{i=0}^{N} \int_{Q} f^{(i)}(x,y,z)dx\\
+=&\sum_{i=0}^{N} a^{(i)} \int_{Q}
+exp \left[ - \left(
+\frac{(x - x_0^{(i)})^2}{2 (\sigma_x^{(i)})^2} +
+\frac{(y - y_0^{(i)})^2}{2 (\sigma_y^{(i)})^2} +
+\frac{(z - z_0^{(i)})^2}{2 (\sigma_z^{(i)})^2}
+\right) \right] dx \\
+=& \sum_{i=0}^{N} a^{(i)} \int_{a_1}^{b_1} exp \left[ - \frac{(x - x_0^{(i)})^2}{2 (\sigma_x^{(i)})^2} \right] dx
+ \int_{a_2}^{b_2}exp \left[ -\frac{(y - y_0^{(i)})^2}{2 (\sigma_y^{(i)})^2} \right]dx
+ \int_{a_3}^{b_3}exp \left[ -\frac{(z - z_0^{(i)})^2}{2 (\sigma_z^{(i)})^2} \right]dx.
+\f}
+
+So we calculate three one dimensional integrals:
+\f{align*}{
+\int_{a}^{b} & exp \left[ - \frac{(x - x_0^{(i)})^2}{2 (\sigma_x^{(i)})^2} \right] dx \\
+=&\int_{-\infty}^{b} exp \left[ - \frac{(x - x_0^{(i)})^2}{2 (\sigma_x^{(i)})^2} \right] dx - \int_{-\infty}^{a} exp \left[ - \frac{(x - x_0^{(i)})^2}{2 (\sigma_x^{(i)})^2} \right] dx \\
+=& \sigma_x^{(i)} \left[\int_{-\infty}^{(a - x_0^{(i)})/ \sigma_x^{(i)}} e^{-\frac{t^2}{2}} dt
+ - \int_{-\infty}^{(b - x_0^{(i)})/ \sigma_x^{(i)}} e^{-\frac{t^2}{2}}dt \right] \\
+=&\sigma_x^{(i)} \sqrt{(\pi)} \left[ \Phi \left( \frac{(a - x_0^{(i)})^2}{\sigma_x^{(i)}} \right) - \Phi \left ( \frac{(b - x_0^{(i)})^2}{\sigma_x^{(i)}} \right) \right].
+\f}
+
+and become for the integral over \f$ Q \f$:
+
+\f{align*}{
+m_k =& \sum_{i=0}^{N} \sigma_x^{(i)} \sigma_y^{(i)} \sigma_z^{(i)} \pi^{1.5}
+ \left[ \Phi \left( \frac{(a_1 - x_0^{(i)})^2}{\sigma_x^{(i)}} \right) - \Phi \left ( \frac{(b_1 - x_0^{(i)})^2}{\sigma_x^{(i)}} \right) \right]\times \\
+ &\left[ \Phi \left( \frac{(a_2 - y_0^{(i)})^2}{\sigma_y^{(i)}} \right) - \Phi \left ( \frac{(b_2 - y_0^{(i)})^2}{\sigma_y^{(i)}} \right) \right]\times
+ \left[ \Phi \left( \frac{(a_3 - z_0^{(i)})^2}{\sigma_z^{(i)}} \right) - \Phi \left ( \frac{(b_3 - z_0^{(i)})^2}{\sigma_z^{(i)}} \right) \right].
+\f}
+
+For the integral over the prism we take the half of the integral over the corresponding cuboid.
+
+Altogether we find the mean value in the sphere as:
+\f{align*}{
+\left( \sum_{Q_k \text{ Cuboid}} m_k + \sum_{P_l \text{ Prism}} 0.5 m_l \right )/Volume(B),
+\f}
+
+where Volume(B) is the volume of the body that approximate the sphere.
+
+Now we know how to calculate the mean value in a sphere for given midpoint and radius. So we assume each voxel in the given image to be the sphere midpoint and we calculate the mean value as described above. If the new mean value is greater than the "maximum-until-now", we take the new value to be the "maximum-until-now". Then we go to the next voxel and make the same calculation and so on. At the same time we save the coordinates of the midpoint voxel.
+
+After we found the midpoint and the maximal mean value, we can calculate the maximum and the minimum in the sphere: we just traverse all the voxels in the region and take the maximum and minimum value and the respective coordinates.
+
+\section Input-and-output Input and output
+
+An example for an input in the command-line is:
+\verbatim
+ mitkMultiGaussianTest C:/temp/outputFile C:/temp/inputFile.xml
+\endverbatim
+
+Here is outputFile the name of the gaussian image with extension .nrrd and at the same time the name of the output file with extension .xml, which is the same as the inputFile, only added the calculated mean value, max and min and the corresponding indexes in the statistic tag. Here we see an example for the input and output .xml file:
+
+\verbatim
+INPUT:
+
+
+
+
+
+
+
+
+
+
+\endverbatim
+
+\verbatim
+OUTPUT:
+
+
+
+
+
+
+
+
+
+
+
+\endverbatim
+
+\subsection Parameter-for-the-input Parameter for the input
+
+In the tag \a testimage we describe the image that we generate. Image rows/columns/slices gives the number of rows/columns/slices of the image; \a numberOfGaussians is the number of gauss functions (\f$ N \f$); spacing defines the extend of one voxel for each direction. The parameter \a entireHotSpotInImage determines whether the whole sphere is in the image included (\f$ = 1 \f$) or only the midpoint of the sphere is inside the image.
+
+NOTE: When the \a entireHotSpotInImage \f$ = 0 \f$ it is possible that we find the midpoint of the sphere on the border of the image. In this case we cut the approximation of the sphere, so that we become a body, which is completely inside the image, but not a "sphere" anymore. To that effect is the volume of the body decreased and that could lead to unexpected results.
+
+In the subtag \a gaussian we describe each gauss function as mentioned in the second section.
+
+In the tag \a segmentation we define the radius of the wanted sphere in mm (\a hotspotRadiusInMM ). We can also set the number of labels (\a numberOfLabels ) to be an positive number and this determines the number of regions of interest (ROI). In each ROI we find the sphere with the wanted properties and midpoint inside the ROI, but not necessarily the whole sphere. In the subtag \a roi we set label number and the index coordinates for the borders of the roi.
+
+*/
+template< typename TOutputImage >
+class ITK_EXPORT MultiGaussianImageSource:public ImageSource< TOutputImage >
+{
+public:
+ /** Standard class typedefs. */
+ typedef MultiGaussianImageSource Self;
+ typedef ImageSource< TOutputImage > Superclass;
+ typedef SmartPointer< Self > Pointer;
+ typedef SmartPointer< const Self > ConstPointer;
+
+ /** Typedef for the output image PixelType. */
+ typedef typename TOutputImage::PixelType OutputImagePixelType;
+
+ /** Typedef to describe the output image region type. */
+ typedef typename TOutputImage::RegionType OutputImageRegionType;
+
+ /** Method for creation through the object factory. */
+ itkNewMacro(Self);
+
+ /** Basic types from the OutputImageType */
+ typedef typename TOutputImage::SizeType SizeType;
+ typedef typename TOutputImage::IndexType IndexType;
+ typedef typename TOutputImage::SpacingType SpacingType;
+ typedef typename TOutputImage::PointType PointType;
+ typedef typename SizeType::SizeValueType SizeValueType;
+ typedef SizeValueType SizeValueArrayType[TOutputImage::ImageDimension];
+ typedef typename TOutputImage::SpacingValueType SpacingValueType;
+ typedef SpacingValueType SpacingValueArrayType[TOutputImage::ImageDimension];
+ typedef typename TOutputImage::PointValueType PointValueType;
+ typedef PointValueType PointValueArrayType[TOutputImage::ImageDimension];
+ typedef typename itk::ImageRegion<3> ::SizeValueType SizeRegionType;
+ /** Typedef to describe the sphere radius type. */
+ typedef double RadiusType;
+ /** Typedef to describe the standard vector type. */
+ typedef std::vector VectorType;
+ /** Typedef to describe the itk vector type. */
+ typedef Vector ItkVectorType;
+ /** Typedef to describe the ImageRegionIteratorWithIndex type. */
+ typedef ImageRegionIteratorWithIndex IteratorType;
+ /** Typedef to describe the Poiner type at the output image. */
+ typedef typename TOutputImage::Pointer ImageType;
+
+ typedef MapContainer MapContainerPoints;
+ typedef MapContainer MapContainerRadius;
+
+
+ /** Set/Get size of the output image. */
+ itkSetMacro(Size, SizeType);
+ virtual void SetSize(SizeValueArrayType sizeArray);
+ virtual const SizeValueType * GetSize() const;
+ /** Set/Get spacing of the output image. */
+ itkSetMacro(Spacing, SpacingType);
+ virtual void SetSpacing(SpacingValueArrayType spacingArray);
+ virtual const SpacingValueType * GetSpacing() const;
+ /** Set/Get origin of the output image. This programm works proper only with origin [0.0, 0.0, 0.0] */
+ itkSetMacro(Origin, PointType);
+ virtual void SetOrigin(PointValueArrayType originArray);
+ virtual const PointValueType * GetOrigin() const;
+ /** Get the number of gaussian functions in the output image. */
+ virtual unsigned int GetNumberOfGaussians() const;
+ /** Set the number of gaussian function. */
+ virtual void SetNumberOfGausssians( unsigned int );
+ /** Set/Get the radius of the sphere. */
+ virtual RadiusType GetRadius() const;
+ virtual void SetRadius( RadiusType radius );
+ /** Get the maximal mean value in a sphere over all possible spheres with midpoint in the image. */
+ virtual const OutputImagePixelType GetMaxMeanValue() const;
+ /** Get the index of the midpoint of a sphere with the maximal mean value.*/
+ virtual const IndexType GetSphereMidpoint() const;
+ /** Calculates the value of the multigaussian function at a Point given by its coordinates [x, y, z]. */
+ virtual double MultiGaussianFunctionValueAtPoint(double , double, double);
+ /** Adds a multigaussian defined by the parameter: CenterX, CenterY, CenterZ, SigmaX, SigmaY, SigmaZ, Altitude.
+ All parameters should have the same size, which determinates the number of the gaussian added. */
+ virtual void AddGaussian( VectorType centerX, VectorType centerY, VectorType centerZ, VectorType sigmaX, VectorType sigmaY, VectorType sigmaZ, VectorType altitude);
+ /** Calculates and set the index of the midpoint of the sphere with the maximal mean value as well as the mean value. */
+ virtual void CalculateTheMidpointAndTheMeanValueWithOctree();
+ /** Calculates and set the index an the value of maximulm and minimum in the wanted sphere. */
+ virtual void CalculateMaxAndMinInSphere();
+ /** Get the index in the sphere with maximal value. */
+ virtual const IndexType GetMaxValueIndexInSphere() const;
+ /** Get the maximal value in the sphere. */
+ virtual const OutputImagePixelType GetMaxValueInSphere() const;
+ /** Get the index in the sphere with minimal value. */
+ virtual const IndexType GetMinValueIndexInSphere() const;
+ /** Get the minimal value in the sphere. */
+ virtual const OutputImagePixelType GetMinValueInSphere() const;
+ /** Set the region of interest. */
+ virtual void SetRegionOfInterest(ItkVectorType, ItkVectorType);
+ /** Write a .mps file to visualise the point in the sphere. */
+ virtual void WriteXMLToTestTheCuboidInsideTheSphere();
+ /**This recursive method realise the octree method. It subdivide a cuboid in eight cuboids, when this cuboid crosses the boundary of sphere. If the cuboid is inside the sphere, it calculates the integral. */
+ virtual void CalculateEdgesInSphere( PointType globalCoordinateMidpointCuboid, PointType globalCoordinateMidpointSphere, double cuboidRadius, int level);
+ /**Calculate and return value of the integral of the gaussian in a cuboid region with the dimension 3: in the x-axis between xMin and xMax and in the y-axis between yMin and yMax and in the z-axis also between zMin and zMax. */
+ virtual double MultiGaussianFunctionValueAtCuboid(double xMin, double xMax, double yMin, double yMax, double zMin, double zMax);
+ /** Inseret the midpoints of cuboid in a vector m_Midpoints, so that we can visualise it. */
+ virtual void InsertPoints( PointType globalCoordinateMidpointCuboid, double cuboidRadius);
+ /** Start the octree recursion in eigth directions for the sphere with midpoint globalCoordinateMidpointSphere. */
+ virtual void GenerateCuboidSegmentationInSphere( PointType globalCoordinateMidpointSphere );
+ /** Get the the values of the cumulative distribution function of the normal distribution. */
+ virtual double FunctionPhi(double value);
+ /** Check if a cuboid with midpoint globalCoordinateMidpointCuboid and side length sideLength intersect the sphere with midpoint globalCoordinateMidpointSphere boundary. */
+ virtual unsigned int IntersectTheSphere( PointType globalCoordinateMidpointCuboid, PointType globalCoordinateMidpointSphere, double sideLength);
+ /** Set the tabel values of the distribution function of the normal distribution. */
+ void SetNormalDistributionValues();
+
+
+ /** Set the minimum possible pixel value. By default, it is
+ * NumericTraits::min(). */
+ itkSetClampMacro( Min, OutputImagePixelType,
+ NumericTraits< OutputImagePixelType >::NonpositiveMin(),
+ NumericTraits< OutputImagePixelType >::max() );
+ /** Check if a index is inside the image*/
+ bool IsInImage(IndexType index);
+
+ /** Get the minimum possible pixel value. */
+ itkGetConstMacro(Min, OutputImagePixelType);
+
+ /** Set the maximum possible pixel value. By default, it is
+ * NumericTraits::max(). */
+ itkSetClampMacro( Max, OutputImagePixelType,
+ NumericTraits< OutputImagePixelType >::NonpositiveMin(),
+ NumericTraits< OutputImagePixelType >::max() );
+
+ /** Get the maximum possible pixel value. */
+ itkGetConstMacro(Max, OutputImagePixelType);
+
+protected:
+ MultiGaussianImageSource();
+ ~MultiGaussianImageSource();
+ void PrintSelf(std::ostream & os, Indent indent) const;
+
+ virtual void GenerateData();
+ virtual void GenerateOutputInformation();
+
+private:
+ MultiGaussianImageSource(const MultiGaussianImageSource &); //purposely not implemented
+ void operator=(const MultiGaussianImageSource &); //purposely not implemented
+
+ SizeType m_Size; //size of the output image
+ SpacingType m_Spacing; //spacing
+ PointType m_Origin; //origin
+ OutputImagePixelType m_MaxValueInSphere; //maximal value in the wanted sphere
+ IndexType m_MaxValueIndexInSphere; //index of the maximal value in the wanted sphere
+ OutputImagePixelType m_MinValueInSphere; //minimal value in the wanted sphere
+ IndexType m_MinValueIndexInSphere; //index of the minimal value in the wanted sphere
+ unsigned int m_NumberOfGaussians; //number of Gaussians
+ RadiusType m_Radius; //radius of the sphere
+ unsigned int m_RadiusStepNumber; //number of steps to traverse the sphere radius
+ OutputImagePixelType m_MeanValue; //mean value in the wanted sphere
+ OutputImagePixelType m_ValueAtMidpoint; //value at the midpoint of the wanted sphere
+ IndexType m_SphereMidpoint; //midpoint of the wanted sphere
+ VectorType m_SigmaX; //deviation in the x-axis
+ VectorType m_SigmaY; //deviation in the y-axis
+ VectorType m_SigmaZ; //deviation in the z-axis
+ VectorType m_CenterX; //x-coordinate of the mean value of Gaussians
+ VectorType m_CenterY; //y-coordinate of the mean value of Gaussians
+ VectorType m_CenterZ; //z-coordinate of the mean value of Gaussians
+ VectorType m_Altitude; //amplitude
+ ItkVectorType m_RegionOfInterestMax; //maximal values for the coordinates in the region of interest
+ ItkVectorType m_RegionOfInterestMin; //minimal values for the coordinates in the region of interest
+ typename TOutputImage::PixelType m_Min; //minimum possible value
+ typename TOutputImage::PixelType m_Max; //maximum possible value
+ PointType m_GlobalCoordinate; //physical coordiante of the sphere midpoint
+ bool m_WriteMPS; //1 = write a MPS File to visualise the cuboid midpoints of one approximation of the sphere
+ MapContainerPoints m_Midpoints; //the midpoints of the cuboids
+ MapContainerRadius m_RadiusCuboid; //the radius ( = 0.5 * side length) of the cuboids (in the same order as the midpoints in m_Midpoints)
+ double m_Volume; //the volume of the body, that approximize the sphere
+ double m_NormalDistValues [410];//normal distribution values
+ double m_meanValueTemp; //= m_Volume * meanValue in each sphere
+ // The following variables are deprecated, and provided here just for
+ // backward compatibility. It use is discouraged.
+ mutable PointValueArrayType m_OriginArray;
+ mutable SpacingValueArrayType m_SpacingArray;
+};
+
+} // end namespace itk
+
+#ifndef ITK_MANUAL_INSTANTIATION
+#include "itkMultiGaussianImageSource.hxx"
+#endif
+
+#endif
diff --git a/Modules/ImageStatistics/itkMultiGaussianImageSource.hxx b/Modules/ImageStatistics/itkMultiGaussianImageSource.hxx
new file mode 100644
index 0000000000..330b9941cb
--- /dev/null
+++ b/Modules/ImageStatistics/itkMultiGaussianImageSource.hxx
@@ -0,0 +1,1004 @@
+/*=========================================================================
+*
+* Copyright Insight Software Consortium
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0.txt
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*
+*=========================================================================*/
+/*=========================================================================
+*
+* Portions of this file are subject to the VTK Toolkit Version 3 copyright.
+*
+* Copyright (c) Ken Martin, Will Schroeder, Bill Lorensen
+*
+* For complete copyright, license and disclaimer of warranty information
+* please refer to the NOTICE file at the top of the ITK source tree.
+*
+*=========================================================================*/
+#ifndef __itkMultiGaussianImageSource_hxx
+#define __itkMultiGaussianImageSource_hxx
+#include
+#include
+#include
+#include "itkMultiGaussianImageSource.h"
+#include "itkImageRegionIterator.h"
+#include "itkObjectFactory.h"
+#include "itkProgressReporter.h"
+#include "itkDOMNodeXMLWriter.h"
+#include "stdlib.h"
+
+namespace itk
+{
+ /**
+ *
+ */
+ template< class TOutputImage >
+ MultiGaussianImageSource< TOutputImage >
+ ::MultiGaussianImageSource()
+ {
+ //Initial image is 100 wide in each direction.
+ for ( unsigned int i = 0; i < TOutputImage::GetImageDimension(); i++ )
+ {
+ m_Size[i] = 100;
+ m_Spacing[i] = 1.0;
+ m_Origin[i] = 0.0;
+ m_SphereMidpoint[i] = 0;
+ }
+
+ m_NumberOfGaussians = 0;
+ m_Radius = 1;
+ m_RadiusStepNumber = 5;
+ m_MeanValue = 0;
+
+ m_Min = NumericTraits< OutputImagePixelType >::NonpositiveMin();
+ m_Max = NumericTraits< OutputImagePixelType >::max();
+ }
+ //-----------------------------------------------------------------------------------------------------------------------
+ template< class TOutputImage >
+ MultiGaussianImageSource< TOutputImage >
+ ::~MultiGaussianImageSource()
+ {}
+ //-----------------------------------------------------------------------------------------------------------------------
+ template< class TOutputImage >
+ void
+ MultiGaussianImageSource< TOutputImage >
+ ::SetSize(SizeValueArrayType sizeArray)
+ {
+ const unsigned int count = TOutputImage::ImageDimension;
+ unsigned int i;
+
+ for ( i = 0; i < count; i++ )
+ {
+ if ( sizeArray[i] != this->m_Size[i] )
+ {
+ break;
+ }
+ }
+ if ( i < count )
+ {
+ this->Modified();
+ for ( i = 0; i < count; i++ )
+ {
+ this->m_Size[i] = sizeArray[i];
+ }
+ }
+ }
+
+ template< class TOutputImage >
+ const typename MultiGaussianImageSource< TOutputImage >::SizeValueType *
+ MultiGaussianImageSource< TOutputImage >
+ ::GetSize() const
+ {
+ return this->m_Size.GetSize();
+ }
+ //-----------------------------------------------------------------------------------------------------------------------
+ template< class TOutputImage >
+ void
+ MultiGaussianImageSource< TOutputImage >
+ ::SetSpacing(SpacingValueArrayType spacingArray)
+ {
+ const unsigned int count = TOutputImage::ImageDimension;
+ unsigned int i;
+
+ for ( i = 0; i < count; i++ )
+ {
+ if ( spacingArray[i] != this->m_Spacing[i] )
+ {
+ break;
+ }
+ }
+ if ( i < count )
+ {
+ this->Modified();
+ for ( i = 0; i < count; i++ )
+ {
+ this->m_Spacing[i] = spacingArray[i];
+ }
+ }
+ }
+ //-----------------------------------------------------------------------------------------------------------------------
+ template< class TOutputImage >
+ void
+ MultiGaussianImageSource< TOutputImage >
+ ::SetOrigin(PointValueArrayType originArray)
+ {
+ const unsigned int count = TOutputImage::ImageDimension;
+ unsigned int i;
+
+ for ( i = 0; i < count; i++ )
+ {
+ if ( originArray[i] != this->m_Origin[i] )
+ {
+ break;
+ }
+ }
+ if ( i < count )
+ {
+ this->Modified();
+ for ( i = 0; i < count; i++ )
+ {
+ this->m_Origin[i] = originArray[i];
+ }
+ }
+ }
+ //-----------------------------------------------------------------------------------------------------------------------
+ template< class TOutputImage >
+ const typename MultiGaussianImageSource< TOutputImage >::PointValueType *
+ MultiGaussianImageSource< TOutputImage >
+ ::GetOrigin() const
+ {
+ for ( unsigned int i = 0; i < TOutputImage::ImageDimension; i++ )
+ {
+ this->m_OriginArray[i] = this->m_Origin[i];
+ }
+ return this->m_OriginArray;
+ }
+
+ template< class TOutputImage >
+ const typename MultiGaussianImageSource< TOutputImage >::SpacingValueType *
+ MultiGaussianImageSource< TOutputImage >
+ ::GetSpacing() const
+ {
+ for ( unsigned int i = 0; i < TOutputImage::ImageDimension; i++ )
+ {
+ this->m_SpacingArray[i] = this->m_Spacing[i];
+ }
+ return this->m_SpacingArray;
+ }
+ //-----------------------------------------------------------------------------------------------------------------------
+ /**
+ *
+ */
+ template< class TOutputImage >
+ void
+ MultiGaussianImageSource< TOutputImage >
+ ::PrintSelf(std::ostream & os, Indent indent) const
+ {
+ Superclass::PrintSelf(os, indent);
+ os << indent << "Max: "
+ << static_cast< typename NumericTraits< OutputImagePixelType >::PrintType >( m_Max )
+ << std::endl;
+ os << indent << "Min: "
+ << static_cast< typename NumericTraits< OutputImagePixelType >::PrintType >( m_Min )
+ << std::endl;
+
+ os << indent << "Origin: [";
+ unsigned int ii = 0;
+ while( ii < TOutputImage::ImageDimension - 1 )
+ {
+ os << m_Origin[ii] << ", ";
+ ++ii;
+ }
+ os << m_Origin[ii] << "]" << std::endl;
+
+ os << indent << "Spacing: [";
+ ii = 0;
+ while( ii < TOutputImage::ImageDimension - 1 )
+ {
+ os << m_Spacing[ii] << ", ";
+ ++ii;
+ }
+ os << m_Spacing[ii] << "]" << std::endl;
+
+ os << indent << "Size: [";
+ ii = 0;
+ while( ii < TOutputImage::ImageDimension - 1 )
+ {
+ os << m_Size[ii] << ", ";
+ ++ii;
+ }
+ os << m_Size[ii] << "]" << std::endl;
+ }
+ //-----------------------------------------------------------------------------------------------------------------------
+ template< class TOutputImage >
+ unsigned int
+ MultiGaussianImageSource< TOutputImage >
+ ::GetNumberOfGaussians() const
+ {
+ return this->m_NumberOfGaussians;
+ }
+ //-----------------------------------------------------------------------------------------------------------------------
+ template< class TOutputImage >
+ typename MultiGaussianImageSource< TOutputImage >::RadiusType
+ MultiGaussianImageSource< TOutputImage >
+ ::GetRadius() const
+ {
+ return this->m_Radius;
+ }
+ //-----------------------------------------------------------------------------------------------------------------------
+ template< class TOutputImage >
+ void
+ MultiGaussianImageSource< TOutputImage >
+ ::SetRadius( RadiusType radius )
+ {
+ this->m_Radius = radius;
+ }
+
+ //-----------------------------------------------------------------------------------------------------------------------
+ template< class TOutputImage >
+ void
+ MultiGaussianImageSource< TOutputImage >
+ ::SetNumberOfGausssians( unsigned int n )
+ {
+ this->m_NumberOfGaussians = n;
+ }
+
+ //-----------------------------------------------------------------------------------------------------------------------
+ template< class TOutputImage >
+ void
+ MultiGaussianImageSource< TOutputImage >
+ ::SetRegionOfInterest( ItkVectorType roiMin, ItkVectorType roiMax )
+ {
+ m_RegionOfInterestMax = roiMax;
+ m_RegionOfInterestMin = roiMin;
+ }
+
+ //-----------------------------------------------------------------------------------------------------------------------
+ template< class TOutputImage >
+ const typename MultiGaussianImageSource< TOutputImage >::OutputImagePixelType
+ MultiGaussianImageSource< TOutputImage >
+ ::GetMaxMeanValue() const
+ {
+ return m_MeanValue;
+ }
+ //-----------------------------------------------------------------------------------------------------------------------
+ template< class TOutputImage >
+ const typename MultiGaussianImageSource< TOutputImage >::OutputImagePixelType
+ MultiGaussianImageSource< TOutputImage >
+ ::GetMaxValueInSphere() const
+ {
+ return m_MaxValueInSphere;
+ }
+ //-----------------------------------------------------------------------------------------------------------------------
+ template< class TOutputImage >
+ const typename MultiGaussianImageSource< TOutputImage >::IndexType
+ MultiGaussianImageSource< TOutputImage >
+ ::GetMaxValueIndexInSphere() const
+ {
+ return m_MaxValueIndexInSphere;
+ }
+ //-----------------------------------------------------------------------------------------------------------------------
+ template< class TOutputImage >
+ const typename MultiGaussianImageSource< TOutputImage >::OutputImagePixelType
+ MultiGaussianImageSource< TOutputImage >
+ ::GetMinValueInSphere() const
+ {
+ return m_MinValueInSphere;
+ }
+ //-----------------------------------------------------------------------------------------------------------------------
+ template< class TOutputImage >
+ const typename MultiGaussianImageSource< TOutputImage >::IndexType
+ MultiGaussianImageSource< TOutputImage >
+ ::GetMinValueIndexInSphere() const
+ {
+ return m_MinValueIndexInSphere;
+ }
+ //-----------------------------------------------------------------------------------------------------------------------
+ template< class TOutputImage >
+ const typename MultiGaussianImageSource< TOutputImage >::IndexType
+ MultiGaussianImageSource< TOutputImage >
+ ::GetSphereMidpoint() const
+ {
+ return m_SphereMidpoint;
+ }
+
+ //-----------------------------------------------------------------------------------------------------------------------
+ /* Calculate and return value of the integral of the gaussian in a cuboid region with the dimension 3: in the x-axis between xMin and xMax and in the y-axis between yMin and yMax and in the z-axis also between zMin and zMax. */
+
+ template< class TOutputImage >
+ double
+ MultiGaussianImageSource< TOutputImage >
+ ::MultiGaussianFunctionValueAtCuboid(double xMin, double xMax, double yMin, double yMax, double zMin, double zMax)
+ {
+ double mean = 0;
+ double summand0, summand1, summand2, value, factor;
+ for(unsigned int n = 0; n < m_NumberOfGaussians; ++n)
+ {
+ summand0 = FunctionPhi((xMax - m_CenterX[n]) / m_SigmaX[n] ) - FunctionPhi((xMin - m_CenterX[n]) / m_SigmaX[n] );
+ summand1 = FunctionPhi((yMax - m_CenterY[n]) / m_SigmaY[n] ) - FunctionPhi((yMin - m_CenterY[n]) / m_SigmaY[n] );
+ summand2 = FunctionPhi((zMax - m_CenterZ[n]) / m_SigmaZ[n] ) - FunctionPhi((zMin - m_CenterZ[n]) / m_SigmaZ[n] );
+
+ value = summand0 * summand1 * summand2;
+ factor = (m_SigmaX[n] * m_SigmaY[n] * m_SigmaZ[n] ) * pow(2.0 * itk::Math::pi, 1.5 );
+ mean = mean + factor * value * m_Altitude[n];
+ }
+ return mean;
+ }
+ //---------------------------------------------------------------------------------------------------------------------
+
+ /*
+ Returns the linear interpolation of the values of the standard normal distribution function. This values could be seen in the vector m_NormalDistValues.
+ */
+ template< class TOutputImage >
+ double
+ MultiGaussianImageSource< TOutputImage >
+ ::FunctionPhi(double value)
+ {
+ double phiAtValue;
+
+ //linear interpolation between the values
+ int indexValue = static_cast( 100 * value);
+ if( indexValue > 409 )
+ {
+ return phiAtValue = 1.0;
+ }
+ else if( indexValue < -409 )
+ {
+ return phiAtValue = 0.0;
+ }
+ else if( indexValue == 409 )
+ {
+ return phiAtValue = m_NormalDistValues[409];
+ }
+ else if( indexValue == -409 )
+ {
+ return phiAtValue = 1.0 - m_NormalDistValues[409];
+ }
+ else
+ {
+ bool negative = false;
+ if (indexValue < 0.0)
+ {
+ negative = true;
+ value = -value;
+ }
+ int indexUp = static_cast( 100 * value) + 1;
+ int indexDown = static_cast( 100 * value);
+ double alpha = 100.0 * value - static_cast(indexDown);
+ phiAtValue = (1.0 - alpha) * m_NormalDistValues[indexDown] + alpha * m_NormalDistValues[indexUp] ;
+ if(negative)
+ {
+ phiAtValue = 1.0 - phiAtValue;
+ }
+ return phiAtValue;
+ }
+ }
+
+ //----------------------------------------------------------------------------------------------------------------------
+ /*
+ Set the midpoint of the cuboid in a vector m_Midpoints. This cuboids discretise the sphere with the octree method.
+ Set the radius of the cuboid ( = 0.5 * length of the side of the cuboid ) in the vector m_RadiusCuboid.
+ */
+ template< class TOutputImage >
+ void
+ MultiGaussianImageSource< TOutputImage >
+ ::InsertPoints( PointType globalCoordinateMidpointCuboid, double cuboidRadius)
+ {
+ typename MapContainerPoints::ElementIdentifier id = m_Midpoints.Size();
+ m_Midpoints.InsertElement(id, globalCoordinateMidpointCuboid);
+ m_RadiusCuboid.InsertElement(id, cuboidRadius);
+ }
+
+ //----------------------------------------------------------------------------------------------------------------------
+
+ /* This recursive method realise the octree method. It subdivide a cuboid in eight cuboids, when this cuboid crosses the boundary of sphere. If the cuboid is inside the sphere, it calculates the integral and, if uncommented, insert the midpoint of the cuboid in the m_Midpoints vector.
+ */
+ template< class TOutputImage >
+ void
+ MultiGaussianImageSource< TOutputImage >
+ ::CalculateEdgesInSphere( PointType globalCoordinateMidpointCuboid, PointType globalCoordinateMidpointSphere, double cuboidRadius, int level )
+ {
+ double xMin, xMax, yMin, yMax, zMin, zMax;
+ double cuboidRadiusRecursion = cuboidRadius;
+ PointType newMidpoint;
+
+ int intersect = IntersectTheSphere( globalCoordinateMidpointCuboid, globalCoordinateMidpointSphere, cuboidRadiusRecursion);
+
+ if( (intersect == 1) )
+ {
+ if (level < 4)
+ {
+ // cuboid intersect the sphere -> call CalculateEdgesInSphere (this method) for the subdivided cuboid
+ cuboidRadiusRecursion = cuboidRadiusRecursion / 2.0;
+ for(int i = -1; i < 2; i+=2)
+ {
+ for(int k = -1; k < 2; k+=2)
+ {
+ for(int j = -1; j < 2; j+=2)
+ {
+ newMidpoint[0] = globalCoordinateMidpointCuboid[0] + static_cast(i) * cuboidRadiusRecursion;
+ newMidpoint[1] = globalCoordinateMidpointCuboid[1] + static_cast(k) * cuboidRadiusRecursion;
+ newMidpoint[2] = globalCoordinateMidpointCuboid[2] + static_cast(j) * cuboidRadiusRecursion;
+
+ this->CalculateEdgesInSphere( newMidpoint, globalCoordinateMidpointSphere, cuboidRadiusRecursion, level + 1 );
+ }
+ }
+ }
+ }
+ // last step of recursion -> on the boundary
+ else
+ {
+ // Calculate the integral and take the half of it (because we are on the boundary)
+ xMin = globalCoordinateMidpointCuboid[0] - cuboidRadius;
+ xMax = globalCoordinateMidpointCuboid[0] + cuboidRadius;
+ yMin = globalCoordinateMidpointCuboid[1] - cuboidRadius;
+ yMax = globalCoordinateMidpointCuboid[1] + cuboidRadius;
+ zMin = globalCoordinateMidpointCuboid[2] - cuboidRadius;
+ zMax = globalCoordinateMidpointCuboid[2] + cuboidRadius;
+
+ // size is in index coordinate -> multiply by the spacing -> global coordinate of the image boundary
+ // yz Plane
+ bool yzPlaneNotCrossYSection = xMin >= m_Origin[0] && xMax <= m_Size[0] * m_Spacing[0];
+ // xz Plane
+ bool xzPlaneNotCrossYSection = yMin >= m_Origin[1] && yMax <= m_Size[1] * m_Spacing[1];
+ // xy Plane
+ bool xyPlaneNotCrossZSection = zMin >= m_Origin[2] && zMax <= m_Size[2] * m_Spacing[2];
+
+ //check if the boundary of the integral is inside the image
+ if( yzPlaneNotCrossYSection && xzPlaneNotCrossYSection && xyPlaneNotCrossZSection)
+ {
+
+ //double temp = this->MultiGaussianFunctionValueAtCuboid( xMin, xMax, yMin, yMax, zMin, zMax ) * 0.5;
+ m_meanValueTemp = m_meanValueTemp + this->MultiGaussianFunctionValueAtCuboid( xMin, xMax, yMin, yMax, zMin, zMax ) * 0.5;
+ m_Volume = m_Volume + pow( 2.0 * cuboidRadius, 3.0) / 2.0;
+ }
+ }
+ }
+ else if(intersect == 2)
+ {
+ // cuboid in the sphere
+
+ // To insert the midpoint and the radius of the cuboid in a vector, so that we can visualise the midpoints, uncomment the next line and the line WriteXMLToTestTheCuboidInsideTheSphere();
+ // InsertPoints(globalCoordinateMidpointCuboid, cuboidRadius);
+
+ // Calculate the integral boundary
+ xMin = globalCoordinateMidpointCuboid[0] - cuboidRadius;
+ xMax = globalCoordinateMidpointCuboid[0] + cuboidRadius;
+ yMin = globalCoordinateMidpointCuboid[1] - cuboidRadius;
+ yMax = globalCoordinateMidpointCuboid[1] + cuboidRadius;
+ zMin = globalCoordinateMidpointCuboid[2] - cuboidRadius;
+ zMax = globalCoordinateMidpointCuboid[2] + cuboidRadius;
+
+ // size is in index coordinate -> multiply by the spacing -> global coordinate of the image boundary
+ // yz Plane
+// bool yzPlaneAtOriginCrossXSection = xMin <= m_Origin[0] && xMax >= m_Origin[0];
+// bool yzPlaneAtImageBorderCrossXSection = xMin <= m_Size[0] * m_Spacing[0] && xMax >= m_Size[0] * m_Spacing[0];
+ bool yzPlaneNotCrossYSection = xMin >= m_Origin[0] && xMax <= m_Size[0] * m_Spacing[0];
+ // xz Plane
+// bool xzPlaneAtOriginCrossYSection = yMin <= m_Origin[1] && yMax >= m_Origin[1];
+// bool xzPlaneAtImageBorderCrossYSection = yMin <= m_Size[1] * m_Spacing[1] && yMax >= m_Size[1] * m_Spacing[1];
+ bool xzPlaneNotCrossYSection = yMin >= m_Origin[1] && yMax <= m_Size[1] * m_Spacing[1];
+ // xy Plane
+// bool xyPlaneAtOriginCrossZSection = zMin <= m_Origin[2] && zMax >= m_Origin[2];
+// bool xyPlaneAtImageBorderCrossZSection = zMin <= m_Size[2] * m_Spacing[2] && zMax >= m_Size[2] * m_Spacing[2];
+ bool xyPlaneNotCrossZSection = zMin >= m_Origin[2] && zMax <= m_Size[2] * m_Spacing[2];
+
+ if( yzPlaneNotCrossYSection && xzPlaneNotCrossYSection && xyPlaneNotCrossZSection)
+ {
+ m_meanValueTemp = m_meanValueTemp + this->MultiGaussianFunctionValueAtCuboid( xMin, xMax, yMin, yMax, zMin, zMax );
+ m_Volume = m_Volume + pow( 2.0 * cuboidRadius, 3.0);
+ }
+ // check if the boundary of the image intersect the cuboid and if yes, change the limits of the cuboid to be only inside the image; therefor we cut the sphere and neglect the part of it outside the image
+
+ else
+ /*
+ if( // one plane crosses the cuboid
+ ( (yzPlaneAtOriginCrossXSection && xzPlaneNotCrossYSection && xyPlaneNotCrossZSection) ||
+ (yzPlaneAtImageBorderCrossXSection && xzPlaneNotCrossYSection && xyPlaneNotCrossZSection) ||
+
+ (yzPlaneNotCrossYSection && xzPlaneAtOriginCrossYSection && xyPlaneNotCrossZSection) ||
+ (yzPlaneNotCrossYSection && xzPlaneAtImageBorderCrossYSection && xyPlaneNotCrossZSection) ||
+
+ (yzPlaneNotCrossYSection && xzPlaneNotCrossYSection && xyPlaneAtOriginCrossZSection) ||
+ (yzPlaneNotCrossYSection && xzPlaneNotCrossYSection && xyPlaneAtImageBorderCrossZSection) )
+ || // two plane cross the cuboid (on the image edges possible)
+ ( (yzPlaneAtOriginCrossXSection && xzPlaneAtOriginCrossYSection && xyPlaneNotCrossZSection) ||
+ ( (yzPlaneAtOriginCrossXSection && xzPlaneNotCrossYSection && xyPlaneAtOriginCrossZSection) ||
+ (yzPlaneAtImageBorderCrossXSection && xzPlaneAtImageBorderCrossYSection && xyPlaneNotCrossZSection) ||
+ (yzPlaneAtImageBorderCrossXSection && xzPlaneNotCrossYSection && xyPlaneAtImageBorderCrossZSection) ||
+
+ (yzPlaneNotCrossYSection && xzPlaneAtOriginCrossYSection && xyPlaneNotCrossZSection) ||
+ (yzPlaneNotCrossYSection && xzPlaneAtOriginCrossYSection && xyPlaneAtOriginCrossZSection) ||
+ (yzPlaneAtImageBorderCrossXSection && xzPlaneAtImageBorderCrossYSection && xyPlaneNotCrossZSection) ||
+ (yzPlaneNotCrossYSection && xzPlaneAtImageBorderCrossYSection && xyPlaneAtImageBorderCrossZSection) ||
+
+ (yzPlaneNotCrossYSection && xzPlaneAtImageBorderCrossYSection && xyPlaneAtOriginCrossZSection) ||
+ (yzPlaneAtOriginCrossXSection && xzPlaneNotCrossYSection && xyPlaneAtOriginCrossZSection) ||
+ (yzPlaneNotCrossYSection && xzPlaneAtImageBorderCrossYSection && xyPlaneAtImageBorderCrossZSection)) ||
+ (yzPlaneAtImageBorderCrossXSection && xzPlaneNotCrossYSection && xyPlaneAtImageBorderCrossZSection) )
+ )
+ */
+ {
+ // x-Axis
+ if(xMin <= m_Origin[0] && xMax >= m_Origin[0])
+ {
+ xMin = m_Origin[0];
+ }else if(xMin <= m_Size[0] * m_Spacing[0] && xMax >= m_Size[0] * m_Spacing[0])
+ {
+ xMax = m_Size[0] * m_Spacing[0];
+ }
+ // y-Axis
+ if(yMin <= m_Origin[1] && yMax >= m_Origin[1])
+ {
+ yMin = m_Origin[1];
+ }else if(yMin <= m_Size[1] * m_Spacing[1] && yMax >= m_Size[1] * m_Spacing[1])
+ {
+ yMax = m_Size[1] * m_Spacing[1];
+ }
+ // z-Axis
+ if(zMin <= m_Origin[2] && zMax >= m_Origin[2])
+ {
+ zMin = m_Origin[2];
+ }else if(zMin <= m_Size[2] * m_Spacing[2] && zMax >= m_Size[2] * m_Spacing[2])
+ {
+ zMax = m_Size[2] * m_Spacing[2];
+ }
+ m_meanValueTemp = m_meanValueTemp + this->MultiGaussianFunctionValueAtCuboid( xMin, xMax, yMin, yMax, zMin, zMax );
+ m_Volume = m_Volume + (xMax - xMin) * (yMax - yMin) * (zMax - zMin) ;
+
+ }
+ }
+ }
+
+ //-----------------------------------------------------------------------------------------------------------------------
+ /* Start the octree recursion in eigth directions for the sphere with midpoint globalCoordinateMidpointSphere and, if uncommented, write this in a file, so that we can visualise it. */
+ template< class TOutputImage >
+ void
+ MultiGaussianImageSource< TOutputImage >
+ ::GenerateCuboidSegmentationInSphere(PointType globalCoordinateMidpointSphere)
+ {
+ double cuboidRadius = m_Radius * 0.5;
+ PointType newMidpoint;
+ for(int i = -1; i < 2; i+=2)
+ {
+ for(int k = -1; k < 2; k+=2)
+ {
+ for(int j = -1; j < 2; j+=2)
+ {
+ newMidpoint[0] = globalCoordinateMidpointSphere[0] + static_cast(i) * cuboidRadius;
+ newMidpoint[1] = globalCoordinateMidpointSphere[1] + static_cast(k) * cuboidRadius;
+ newMidpoint[2] = globalCoordinateMidpointSphere[2] + static_cast(j) * cuboidRadius;
+
+ CalculateEdgesInSphere( newMidpoint, globalCoordinateMidpointSphere, cuboidRadius, 0);
+ }
+ }
+ }
+
+ if(m_WriteMPS)
+ {
+ m_WriteMPS = 0;
+ // uncomment to write an .mps file to visualise the midpoints
+ // std::cout << "Wrote .xml to visualise the midpoints." << std::endl;
+ // WriteXMLToTestTheCuboidInsideTheSphere();
+ }
+ }
+
+ //----------------------------------------------------------------------------------------------------------------------
+ /* This class allows by the method CalculateTheMidpointAndTheMeanValueWithOctree() to find a sphere with a specified radius that has a maximal mean value over all sphere with that radius with midpoint inside or at the boundary of the image. We approximaze the sphere with the octree recursiv method.
+ CalculateTheMidpointAndTheMeanValueWithOctree works as follows:
+ 1. The for-loops traverse the region of interest and assume the current point to be the wanted sphere midpoint.
+ 2. Calculate the mean value for that sphere.
+ 3. Compare with the until-now-found-maximum and take the bigger one. */
+ template< class TOutputImage >
+ void
+ MultiGaussianImageSource< TOutputImage >
+ ::CalculateTheMidpointAndTheMeanValueWithOctree()
+ {
+
+ m_MeanValue = 0.0;
+ double meanValueTemp;
+ PointType midpoint;
+ //typename MapContainerPoints::ElementIdentifier cuboidNumber = m_Midpoints.Size();
+ // SetNormalDistributionValues();
+ //double radius;
+ //double xMin, xMax, yMin, yMax, zMin, zMax;
+
+ m_WriteMPS = 1;
+ PointType globalCoordinateMidpointSphere;
+ IndexType index;
+ OutputImageRegionType regionOfInterest;
+ IndexType indexR;
+ indexR.SetElement( 0, m_RegionOfInterestMin[0] );
+ indexR.SetElement( 1, m_RegionOfInterestMin[1] );
+ indexR.SetElement( 2, m_RegionOfInterestMin[2] );
+ regionOfInterest.SetIndex(indexR);
+ SizeType sizeROI;
+ sizeROI.SetElement( 0, m_RegionOfInterestMax[0] - m_RegionOfInterestMin[0] + 1);
+ sizeROI.SetElement( 1, m_RegionOfInterestMax[1] - m_RegionOfInterestMin[1] + 1);
+ sizeROI.SetElement( 2, m_RegionOfInterestMax[2] - m_RegionOfInterestMin[2] + 1);
+ regionOfInterest.SetSize(sizeROI);
+ typename TOutputImage::Pointer image = this->GetOutput(0);
+ IteratorType regionOfInterestIterator(image, regionOfInterest);
+
+ for(regionOfInterestIterator.GoToBegin(); !regionOfInterestIterator.IsAtEnd(); ++regionOfInterestIterator)
+ {
+ index = regionOfInterestIterator.GetIndex();
+ image->TransformIndexToPhysicalPoint(index, globalCoordinateMidpointSphere);
+ m_Volume = 0.0;
+ m_meanValueTemp = 0.0;
+ this->GenerateCuboidSegmentationInSphere(globalCoordinateMidpointSphere);
+ meanValueTemp = m_meanValueTemp / m_Volume;
+ // std::cout << "index: " << index <<" meanvalue: " << meanValueTemp << std::endl;
+ if(meanValueTemp > m_MeanValue)
+ {
+ m_GlobalCoordinate = globalCoordinateMidpointSphere;
+ m_MeanValue = meanValueTemp;
+ m_SphereMidpoint = index;
+ }
+ }
+ }
+
+ //----------------------------------------------------------------------------------------------------------------------
+ /*
+ Check if a cuboid intersect the sphere boundary. Returns 2, if the cuboid is inside the sphere; returns 1, if the cuboid intersects the sphere boundary and 0, if the cuboid is out of the sphere.
+ */
+ template< class TOutputImage >
+ unsigned int
+ MultiGaussianImageSource< TOutputImage >
+ ::IntersectTheSphere( PointType globalCoordinateMidpointCuboid, PointType globalCoordinateMidpointSphere, double cuboidRadius)
+ {
+ unsigned int intersect = 1;
+ PointType cuboidEdge;
+ int count = 0;
+
+ for(int i = -1; i < 2; i+=2)
+ {
+ for(int k = -1; k < 2; k+=2)
+ {
+ for(int j = -1; j < 2; j+=2)
+ {
+ cuboidEdge[0] = globalCoordinateMidpointCuboid[0] + static_cast(i) * cuboidRadius;
+ cuboidEdge[1] = globalCoordinateMidpointCuboid[1] + static_cast(k) * cuboidRadius;
+ cuboidEdge[2] = globalCoordinateMidpointCuboid[2] + static_cast(j) * cuboidRadius;
+
+ if (globalCoordinateMidpointSphere.SquaredEuclideanDistanceTo(cuboidEdge) <= m_Radius * m_Radius)
+ {
+ ++count;
+ }
+ }
+ }
+ }
+ if ( count == 0 )
+ {
+ // cuboid not in the sphere
+ intersect = 0;
+ }
+ if (count == 8 )
+ {
+ // cuboid in the sphere
+ intersect = 2;
+ }
+ return intersect;
+ }
+
+ //----------------------------------------------------------------------------------------------------------------------
+ template< class TOutputImage >
+ double
+ MultiGaussianImageSource< TOutputImage >
+ ::MultiGaussianFunctionValueAtPoint(double x, double y, double z)
+ {
+ //this claculate the mean value in the voxel
+ //integrate over the voxel with midpoint [x, y, z]
+ double summand0, summand1, summand2/*, power*/, value = 0.0, factor;
+ double xMin, xMax, yMin, yMax, zMin, zMax, mean;
+ mean = 0.0;
+ // the for-loop represent the sum of the gaussian function
+ xMin = x - m_Spacing[0] / 2.0;
+ xMax = x + m_Spacing[0] / 2.0;
+ yMin = y - m_Spacing[1] / 2.0;
+ yMax = y + m_Spacing[1] / 2.0;
+ zMin = z - m_Spacing[2] / 2.0;
+ zMax = z + m_Spacing[2] / 2.0;
+ for( unsigned int n = 0; n < m_NumberOfGaussians; ++n )
+ {
+ summand0 = FunctionPhi( (xMax - m_CenterX[n]) / m_SigmaX[n] ) - FunctionPhi( (xMin - m_CenterX[n]) / m_SigmaX[n] );
+ summand1 = FunctionPhi( (yMax - m_CenterY[n]) / m_SigmaY[n] ) - FunctionPhi( (yMin - m_CenterY[n]) / m_SigmaY[n] );
+ summand2 = FunctionPhi( (zMax - m_CenterZ[n]) / m_SigmaZ[n] ) - FunctionPhi( (zMin - m_CenterZ[n]) / m_SigmaZ[n] );
+ value = summand0 * summand1 * summand2;
+ factor = ( m_SigmaX[n] * m_SigmaY[n] * m_SigmaZ[n] ) * pow( 2.0 * itk::Math::pi, 1.5 );
+ mean = mean + factor * value * m_Altitude[n];
+ }
+ value = mean / (m_Spacing[0] * m_Spacing[1] * m_Spacing[2] );
+
+ /*
+
+ //this calculate the value of the gaussian at the midpoint of the voxel:
+ double summand0, summand1, summand2, power, value = 0.0;
+ // the for-loop represent the sum of the gaussian function
+ for(unsigned int n =0; n < m_NumberOfGaussians; ++n)
+ {
+ summand0 = ( x - m_CenterX[n] ) / m_SigmaX[n];
+ summand1 = ( y - m_CenterY[n] ) / m_SigmaY[n];
+ summand2 = ( z - m_CenterZ[n] ) / m_SigmaZ[n];
+
+ power = summand0 * summand0 + summand1 * summand1 + summand2 * summand2;
+ value = value + m_Altitude[n] * pow(itk::Math::e, -0.5 * power);
+ }
+
+ */
+ // std::cout << "X: " << xMin << " " << x << " "<< xMax << " Y: "<< yMin << " " << y << " " << yMax << " Z: "<< zMin << " "<< z << " " << zMax << " value: " << value << std::endl;
+ return value;
+ }
+
+ //----------------------------------------------------------------------------------------------------------------------
+ template< class TOutputImage >
+ void
+ MultiGaussianImageSource< TOutputImage >
+ ::AddGaussian( VectorType x, VectorType y, VectorType z, VectorType sx, VectorType sy, VectorType sz, VectorType altitude)
+ {
+ for(unsigned int i = 0; i < x.size(); ++i)
+ {
+
+ m_CenterX.push_back( x[i] );
+ m_CenterY.push_back( y[i] );
+ m_CenterZ.push_back( z[i] );
+ m_SigmaX.push_back( sx[i] );
+ m_SigmaY.push_back( sy[i] );
+ m_SigmaZ.push_back( sz[i] );
+ m_Altitude.push_back(altitude[i]);
+ }
+ }
+
+ //-----------------------------------------------------------------------------------------------------------------------
+ template< typename TOutputImage >
+ void
+ MultiGaussianImageSource< TOutputImage >
+ ::GenerateOutputInformation()
+ {
+ TOutputImage *output;
+ IndexType index;
+ index.Fill(0);
+ output = this->GetOutput(0);
+ typename TOutputImage::RegionType largestPossibleRegion;
+ largestPossibleRegion.SetSize(this->m_Size);
+ largestPossibleRegion.SetIndex(index);
+ output->SetLargestPossibleRegion(largestPossibleRegion);
+ output->SetSpacing(m_Spacing);
+ output->SetOrigin(m_Origin);
+ }
+
+ //-----------------------------------------------------------------------------------------------------------------------
+ template< typename TOutputImage >
+ void
+ MultiGaussianImageSource< TOutputImage >
+ ::GenerateData()
+ {
+ itkDebugMacro(<< "Generating a image of scalars ");
+ double valueReal;
+ IndexType index;
+ typedef typename TOutputImage::PixelType scalarType;
+ typename TOutputImage::Pointer image = this->GetOutput(0);
+ image = this->GetOutput(0);
+ image->SetBufferedRegion( image->GetRequestedRegion() );
+ image->Allocate();
+ IteratorType imageIt(image, image->GetLargestPossibleRegion());
+ PointType globalCoordinate;
+ this->SetNormalDistributionValues();
+ for(imageIt.GoToBegin(); !imageIt.IsAtEnd(); ++imageIt)
+ {
+ valueReal = 0.0;
+ index = imageIt.GetIndex();
+ image->TransformIndexToPhysicalPoint(imageIt.GetIndex(), globalCoordinate);
+ valueReal = MultiGaussianFunctionValueAtPoint(globalCoordinate[0], globalCoordinate[1] ,globalCoordinate[2]);
+ imageIt.Set(valueReal);
+ }
+ }
+
+ //-----------------------------------------------------------------------------------------------------------------------
+ /*This method is used to write a .mps file, so that we can visualize the midpoints of the approximated sphere as a scatterplot (for example with MITK Workbench).
+ */
+ template< typename TOutputImage >
+ void
+ MultiGaussianImageSource< TOutputImage >
+ ::WriteXMLToTestTheCuboidInsideTheSphere()
+ {
+ std::stringstream ss;
+
+
+ int numberSummand = 1.0;
+
+ //write an .mps test file
+ itk::DOMNodeXMLWriter::Pointer xmlWriter;
+ typedef itk::DOMNode::Pointer DOMNodeType;
+ DOMNodeType domXML, domPointSetFile, domFileVersion, domPointSet, domPoint, domId, domX, domY, domZ;
+
+ xmlWriter = itk::DOMNodeXMLWriter::New();
+ domXML = itk::DOMNode::New();
+ domXML->SetName("?xml");
+ domPointSetFile = itk::DOMNode::New();
+ domPointSetFile->SetName("point_set_file");
+ //domFileVersion = itk::DOMNode::New();
+ //domFileVersion->SetName("file_version");
+ domPointSet = itk::DOMNode::New();
+ domPointSet->SetName("point_set");
+
+ ss.str("");
+ ss << 1.0;
+ domXML->SetAttribute("version", ss.str());
+ domXML->AddChildAtBegin(domPointSetFile);
+ //domPointSetFile -> AddChildAtBegin(domFileVersion);
+ domPointSetFile -> AddChildAtBegin(domPointSet);
+
+
+ unsigned int cap = m_Midpoints.Size();
+ for(unsigned int iter = 0 ; iter < cap; ++iter)
+ {
+ domPoint = itk::DOMNode::New();
+ domPoint->SetName("point");
+ domX = itk::DOMNode::New();
+ domX->SetName("x");
+ domY = itk::DOMNode::New();
+ domY->SetName("y");
+ domZ = itk::DOMNode::New();
+ domZ->SetName("z");
+ domId = itk::DOMNode::New();
+ domId->SetName("id");
+
+
+ ss.str("");
+ ss << numberSummand;
+ domId->AddTextChildAtBegin(ss.str());
+ domPoint -> AddChildAtEnd(domId);
+
+ double scaleFactor = 10.0;
+ PointType point = m_Midpoints.GetElement( numberSummand - 1 );
+ ss.str("");
+ ss << point[0] * scaleFactor;
+ domX->AddTextChildAtBegin(ss.str());
+ domPoint -> AddChildAtEnd(domX);
+ ss.str("");
+ ss << point[1] * scaleFactor;
+ domY->AddTextChildAtBegin(ss.str());
+ domPoint -> AddChildAtEnd(domY);
+ ss.str("");
+ ss << point[2] * scaleFactor;
+ domZ->AddTextChildAtBegin(ss.str());
+ domPoint -> AddChildAtEnd(domZ);
+ domPointSet -> AddChildAtEnd(domPoint);
+
+ numberSummand += 1.0;
+ }
+
+
+ // .mps (Data)
+ ss.str("");
+ ss << "C:/temp/CuboidsInTheSphere.mps";
+ std::string name = ss.str();
+ char * fileNamePointer = (char*) name.c_str();
+ xmlWriter->SetFileName( fileNamePointer);
+ xmlWriter->SetInput( domXML );
+ xmlWriter->Update();
+
+
+
+
+ }
+
+ //-----------------------------------------------------------------------------------------------------------------------
+ template< typename TOutputImage >
+ void
+ MultiGaussianImageSource< TOutputImage >
+ ::CalculateMaxAndMinInSphere()
+ {
+ IndexType index;
+ MultiGaussianImageSource< TOutputImage >::OutputImagePixelType value;
+ m_MaxValueInSphere = std::numeric_limits::min();
+ m_MinValueInSphere = std::numeric_limits::max();
+ unsigned int radInt, sizeRegion;
+ OutputImageRegionType cuboidRegion;
+ IndexType indexR;
+ SizeType sizeR;
+ int indexRegion, originAsIndex;
+ for( unsigned int i = 0; i < 3; ++i )
+ {
+ radInt = static_cast(m_Radius/m_Spacing[i]);
+ indexRegion = m_SphereMidpoint[i] - radInt;
+ originAsIndex = static_cast(m_Origin[i]/m_Spacing[i]);
+ if( originAsIndex > indexRegion )
+ {
+ indexR.SetElement(i, originAsIndex );
+ }
+ else
+ {
+ indexR.SetElement(i, indexRegion );
+ }
+
+ sizeRegion = 2 *radInt + 1;
+ int sizeOutputImage = m_Size[i];
+ if( (indexR[i] + sizeRegion) > (originAsIndex + sizeOutputImage) )
+ {
+ std::cout << "Not the entire sphere is in the image!" << std::endl;
+ sizeR.SetElement(i, m_Size[i] - indexRegion );
+ }
+ else
+ {
+ sizeR.SetElement(i, sizeRegion );
+ }
+ }
+ cuboidRegion.SetIndex(indexR);
+ cuboidRegion.SetSize(sizeR);
+ typename TOutputImage::Pointer image = this->GetOutput(0);
+ IteratorType cuboidRegionOfInterestIterator(image, cuboidRegion);
+ PointType globalCoordinate;
+ for(cuboidRegionOfInterestIterator.GoToBegin(); !cuboidRegionOfInterestIterator.IsAtEnd(); ++cuboidRegionOfInterestIterator)
+ {
+ index = cuboidRegionOfInterestIterator.GetIndex();
+ if(IsInImage(index))
+ {
+ image->TransformIndexToPhysicalPoint(cuboidRegionOfInterestIterator.GetIndex(), globalCoordinate);
+ if( m_GlobalCoordinate.EuclideanDistanceTo(globalCoordinate) <= m_Radius )
+ {
+ value = cuboidRegionOfInterestIterator.Get();
+ if(m_MaxValueInSphere < value)
+ {
+ m_MaxValueInSphere = value;
+ m_MaxValueIndexInSphere = index;
+ }
+ if(m_MinValueInSphere > value)
+ {
+ m_MinValueInSphere = value;
+ m_MinValueIndexInSphere = index;
+ }
+ }
+ }
+ }
+ }
+
+ //-----------------------------------------------------------------------------------------------------------------------
+ template< typename TOutputImage >
+ bool
+ MultiGaussianImageSource< TOutputImage >
+ ::IsInImage(IndexType index)
+ {
+ bool isInImage = true;
+ int originAsIndex;
+ for( unsigned int i = 0; i < 3; ++i )
+ {
+ originAsIndex = static_cast(m_Origin[i]/m_Spacing[i]);
+ int sizeOfOutputImage = m_Size[i];
+ if( index[i] < originAsIndex || index[i] > (originAsIndex + sizeOfOutputImage) )
+ return false;
+ }
+ return isInImage;
+ }
+
+ //-----------------------------------------------------------------------------------------------------------------------
+ template< typename TOutputImage >
+ void
+ MultiGaussianImageSource< TOutputImage >
+ ::SetNormalDistributionValues()
+ {
+
+ double temp[410] = { 0.5 , 0.50399 , 0.50798, 0.51197, 0.51595, 0.51994, 0.52392, 0.5279, 0.53188, 0.53586, 0.53983, 0.5438, 0.54776, 0.55172, 0.55567, 0.55962, 0.56356, 0.56749, 0.57142, 0.57535, 0.57926, 0.58317, 0.58706, 0.59095, 0.59483 , 0.59871, 0.60257, 0.60642, 0.61026, 0.61409, 0.61791, 0.62172, 0.62552, 0.6293, 0.63307, 0.63683, 0.64058, 0.64431, 0.64803, 0.65173, 0.65542, 0.6591, 0.66276, 0.6664, 0.67003, 0.67364, 0.67724, 0.68082, 0.68439, 0.68793, 0.69146, 0.69497, 0.69847, 0.70194, 0.7054, 0.70884, 0.71226, 0.71566, 0.71904, 0.7224, 0.72575, 0.72907, 0.73237, 0.73565, 0.73891, 0.74215, 0.74537, 0.74857, 0.75175, 0.7549, 0.75804, 0.76115, 0.76424, 0.7673, 0.77035, 0.77337, 0.77637, 0.77935, 0.7823, 0.78524, 0.78814, 0.79103, 0.79389, 0.79673, 0.79955, 0.80234, 0.80511, 0.80785, 0.81057, 0.81327, 0.81594, 0.81859, 0.82121, 0.82381, 0.82639, 0.82894, 0.83147, 0.83398, 0.83646, 0.83891, 0.84134, 0.84375, 0.84614, 0.84849, 0.85083, 0.85314, 0.85543, 0.85769, 0.85993, 0.86214, 0.86433, 0.8665, 0.86864, 0.87076, 0.87286, 0.87493, 0.87698, 0.879, 0.881, 0.88298, 0.88493, 0.88686, 0.88877, 0.89065, 0.89251, 0.89435, 0.89617, 0.89796, 0.89973, 0.90147, 0.9032, 0.9049, 0.90658, 0.90824, 0.90988, 0.91149, 0.91309, 0.91466, 0.91621, 0.91774, 0.91924, 0.92073, 0.9222, 0.92364, 0.92507, 0.92647, 0.92785, 0.92922, 0.93056, 0.93189, 0.93319, 0.93448, 0.93574, 0.93699, 0.93822, 0.93943, 0.94062, 0.94179, 0.94295, 0.94408, 0.9452, 0.9463, 0.94738, 0.94845, 0.9495, 0.95053, 0.95154, 0.95254, 0.95352, 0.95449, 0.95543, 0.95637, 0.95728, 0.95818, 0.95907, 0.95994, 0.9608, 0.96164, 0.96246, 0.96327, 0.96407, 0.96485, 0.96562, 0.96638, 0.96712, 0.96784, 0.96856, 0.96926, 0.96995, 0.97062, 0.97128, 0.97193, 0.97257, 0.9732, 0.97381, 0.97441, 0.975, 0.97558, 0.97615, 0.9767, 0.97725, 0.97778, 0.97831, 0.97882, 0.97932, 0.97982, 0.9803, 0.98077, 0.98124, 0.98169, 0.98214, 0.98257, 0.983, 0.98341, 0.98382, 0.98422, 0.98461, 0.985, 0.98537, 0.98574, 0.9861, 0.98645, 0.98679, 0.98713, 0.98745, 0.98778, 0.98809, 0.9884, 0.9887, 0.98899, 0.98928, 0.98956, 0.98983, 0.9901, 0.99036, 0.99061, 0.99086, 0.99111, 0.99134, 0.99158, 0.9918, 0.99202, 0.99224, 0.99245, 0.99266, 0.99286, 0.99305, 0.99324, 0.99343, 0.99361, 0.99379, 0.99396, 0.99413, 0.9943, 0.99446, 0.99461, 0.99477, 0.99492, 0.99506, 0.9952, 0.99534, 0.99547, 0.9956, 0.99573, 0.99585, 0.99598, 0.99609, 0.99621, 0.99632, 0.99643, 0.99653, 0.99664, 0.99674, 0.99683, 0.99693, 0.99702, 0.99711, 0.9972, 0.99728, 0.99736, 0.99744, 0.99752, 0.9976, 0.99767, 0.99774, 0.99781, 0.99788, 0.99795, 0.99801, 0.99807, 0.99813, 0.99819, 0.99825, 0.99831, 0.99836, 0.99841, 0.99846, 0.99851, 0.99856, 0.99861, 0.99865, 0.99869, 0.99874, 0.99878, 0.99882, 0.99886, 0.99889, 0.99893, 0.99896, 0.999, 0.99903, 0.99906, 0.9991, 0.99913, 0.99916, 0.99918, 0.99921, 0.99924, 0.99926, 0.99929, 0.99931, 0.99934, 0.99936, 0.99938, 0.9994, 0.99942, 0.99944, 0.99946, 0.99948, 0.9995, 0.99952, 0.99953, 0.99955, 0.99957, 0.99958, 0.9996, 0.99961, 0.99962, 0.99964, 0.99965, 0.99966, 0.99968, 0.99969, 0.9997, 0.99971, 0.99972, 0.99973, 0.99974, 0.99975, 0.99976, 0.99977, 0.99978, 0.99978, 0.99979, 0.9998, 0.99981, 0.99981, 0.99982, 0.99983, 0.99983, 0.99984, 0.99985, 0.99985, 0.99986, 0.99986, 0.99987, 0.99987, 0.99988, 0.99988, 0.99989, 0.99989, 0.9999, 0.9999, 0.9999, 0.99991, 0.99991, 0.99992, 0.99992, 0.99992, 0.99992, 0.99993, 0.99993, 0.99993, 0.99994, 0.99994, 0.99994, 0.99994, 0.99995, 0.99995, 0.99995, 0.99995, 0.99995, 0.99996, 0.99996, 0.99996, 0.99996, 0.99996, 0.99996, 0.99997, 0.99997, 0.99997, 0.99997, 0.99997, 0.99997, 0.99997, 0.99997, 0.99998, 0.99998, 0.99998, 0.99998 };
+
+ for(int i=0; i < 410; i++)
+ {
+ m_NormalDistValues[i] = temp[i];
+ }
+
+ }
+
+
+} // end namespace itk
+
+ #endif
diff --git a/Modules/ImageStatistics/mitkImageStatisticsCalculator.cpp b/Modules/ImageStatistics/mitkImageStatisticsCalculator.cpp
index 1f7081ac8b..c27ad0ae8c 100644
--- a/Modules/ImageStatistics/mitkImageStatisticsCalculator.cpp
+++ b/Modules/ImageStatistics/mitkImageStatisticsCalculator.cpp
@@ -1,1304 +1,2010 @@
/*===================================================================
The Medical Imaging Interaction Toolkit (MITK)
Copyright (c) German Cancer Research Center,
Division of Medical and Biological Informatics.
All rights reserved.
This software is distributed WITHOUT ANY WARRANTY; without
even the implied warranty of MERCHANTABILITY or FITNESS FOR
A PARTICULAR PURPOSE.
See LICENSE.txt or http://www.mitk.org for details.
===================================================================*/
#include "mitkImageStatisticsCalculator.h"
#include "mitkImageAccessByItk.h"
#include "mitkImageCast.h"
#include "mitkExtractImageFilter.h"
+#include "mitkImageTimeSelector.h"
+#include "mitkITKImageImport.h"
#include
#include
#include
#include
#include
#include
#include
#include
#include
+#include
+#include
+
#include
-#include
#include
#include
#include
-
#include
#include
#include
#include
#include
#include
#include
#include
#include
#include
#include
+#include
+#include
+#include
+
+#include
+#include
#include
#include
+
namespace mitk
{
-
ImageStatisticsCalculator::ImageStatisticsCalculator()
: m_MaskingMode( MASKING_MODE_NONE ),
m_MaskingModeChanged( false ),
m_IgnorePixelValue(0.0),
m_DoIgnorePixelValue(false),
m_IgnorePixelValueChanged(false),
m_PlanarFigureAxis (0),
m_PlanarFigureSlice (0),
m_PlanarFigureCoordinate0 (0),
m_PlanarFigureCoordinate1 (0),
m_HistogramBinSize(1),
-m_UseDefaultBinSize(true)
+ m_UseDefaultBinSize(true),
+ m_HotspotRadiusInMM(6.2035049089940), // radius of a 1cm3 sphere in mm
+ m_CalculateHotspot(false),
+ m_HotspotRadiusInMMChanged(false),
+ m_HotspotMustBeCompletelyInsideImage(true)
{
m_EmptyHistogram = HistogramType::New();
m_EmptyHistogram->SetMeasurementVectorSize(1);
HistogramType::SizeType histogramSize(1);
histogramSize.Fill( 256 );
m_EmptyHistogram->Initialize( histogramSize );
m_EmptyStatistics.Reset();
-}
+}
ImageStatisticsCalculator::~ImageStatisticsCalculator()
{
}
void ImageStatisticsCalculator::SetUseDefaultBinSize(bool useDefault)
{
m_UseDefaultBinSize = useDefault;
}
+ImageStatisticsCalculator::Statistics::Statistics(bool withHotspotStatistics)
+:m_HotspotStatistics(withHotspotStatistics ? new Statistics(false) : NULL)
+{
+ Reset();
+}
+
+ImageStatisticsCalculator::Statistics::Statistics(const Statistics& other)
+:m_HotspotStatistics( NULL)
+{
+ this->SetLabel( other.GetLabel() );
+ this->SetN( other.GetN() );
+ this->SetMin( other.GetMin() );
+ this->SetMax( other.GetMax() );
+ this->SetMedian( other.GetMedian() );
+ this->SetMean( other.GetMean() );
+ this->SetVariance( other.GetVariance() );
+ this->SetSigma( other.GetSigma() );
+ this->SetRMS( other.GetRMS() );
+ this->SetMaxIndex( other.GetMaxIndex() );
+ this->SetMinIndex( other.GetMinIndex() );
+ this->SetHotspotIndex( other.GetHotspotIndex() );
+
+ if (other.m_HotspotStatistics)
+ {
+ this->m_HotspotStatistics = new Statistics(false);
+ *this->m_HotspotStatistics = *other.m_HotspotStatistics;
+ }
+}
+
+bool ImageStatisticsCalculator::Statistics::HasHotspotStatistics() const
+{
+ return m_HotspotStatistics != NULL;
+}
+
+void ImageStatisticsCalculator::Statistics::SetHasHotspotStatistics(bool hasHotspotStatistics)
+{
+ m_HasHotspotStatistics = hasHotspotStatistics;
+}
+
+
+ImageStatisticsCalculator::Statistics::~Statistics()
+{
+ delete m_HotspotStatistics;
+}
+
+double ImageStatisticsCalculator::Statistics::GetVariance() const
+{
+ return this->Variance;
+}
+
+void ImageStatisticsCalculator::Statistics::SetVariance( const double value )
+{
+ if( this->Variance != value )
+ {
+ if( value < 0.0 )
+ {
+ this->Variance = 0.0; // if given value is negative set variance to 0.0
+ }
+ else
+ {
+ this->Variance = value;
+ }
+ }
+}
+
+double ImageStatisticsCalculator::Statistics::GetSigma() const
+{
+ return this->Sigma;
+}
+
+void ImageStatisticsCalculator::Statistics::SetSigma( const double value )
+{
+ if( this->Sigma != value )
+ {
+ // for some compiler the value != value works to check for NaN but not for all
+ // but we can always be sure that the standard deviation is a positive value
+ if( value != value || value < 0.0 )
+ {
+ // if standard deviation is NaN we just assume 0.0
+ this->Sigma = 0.0;
+ }
+ else
+ {
+ this->Sigma = value;
+ }
+ }
+}
+
+void ImageStatisticsCalculator::Statistics::Reset(unsigned int dimension)
+{
+ SetLabel(0);
+ SetN( 0 );
+ SetMin( 0.0 );
+ SetMax( 0.0 );
+ SetMedian( 0.0 );
+ SetVariance( 0.0 );
+ SetMean( 0.0 );
+ SetSigma( 0.0 );
+ SetRMS( 0.0 );
+
+ vnl_vector zero;
+ zero.set_size(dimension);
+ for(unsigned int i = 0; i < dimension; ++i)
+ {
+ zero[i] = 0;
+ }
+
+ SetMaxIndex(zero);
+ SetMinIndex(zero);
+ SetHotspotIndex(zero);
+
+ if (m_HotspotStatistics != NULL)
+ {
+ m_HotspotStatistics->Reset(dimension);
+ }
+}
+
+const ImageStatisticsCalculator::Statistics&
+ImageStatisticsCalculator::Statistics::GetHotspotStatistics() const
+{
+ if (m_HotspotStatistics)
+ {
+ return *m_HotspotStatistics;
+ }
+ else
+ {
+ throw std::logic_error("Object has no hostspot statistics, see HasHotspotStatistics()");
+ }
+}
+
+ImageStatisticsCalculator::Statistics&
+ImageStatisticsCalculator::Statistics::GetHotspotStatistics()
+{
+ if (m_HotspotStatistics)
+ {
+ return *m_HotspotStatistics;
+ }
+ else
+ {
+ throw std::logic_error("Object has no hostspot statistics, see HasHotspotStatistics()");
+ }
+}
+
+ImageStatisticsCalculator::Statistics&
+ImageStatisticsCalculator::Statistics::operator=(ImageStatisticsCalculator::Statistics const& other)
+{
+ if (this == &other)
+ return *this;
+
+ this->SetLabel( other.GetLabel() );
+ this->SetN( other.GetN() );
+ this->SetMin( other.GetMin() );
+ this->SetMax( other.GetMax() );
+ this->SetMean( other.GetMean() );
+ this->SetMedian( other.GetMedian() );
+ this->SetVariance( other.GetVariance() );
+ this->SetSigma( other.GetSigma() );
+ this->SetRMS( other.GetRMS() );
+ this->SetMinIndex( other.GetMinIndex() );
+ this->SetMaxIndex( other.GetMaxIndex() );
+ this->SetHotspotIndex( other.GetHotspotIndex() );
+
+ delete this->m_HotspotStatistics;
+ this->m_HotspotStatistics = NULL;
+
+ if (other.m_HotspotStatistics)
+ {
+ this->m_HotspotStatistics = new Statistics(false);
+ *this->m_HotspotStatistics = *other.m_HotspotStatistics;
+ }
+
+ return *this;
+
+}
+
void ImageStatisticsCalculator::SetImage( const mitk::Image *image )
{
if ( m_Image != image )
{
m_Image = image;
this->Modified();
unsigned int numberOfTimeSteps = image->GetTimeSteps();
// Initialize vectors to time-size of this image
m_ImageHistogramVector.resize( numberOfTimeSteps );
m_MaskedImageHistogramVector.resize( numberOfTimeSteps );
m_PlanarFigureHistogramVector.resize( numberOfTimeSteps );
m_ImageStatisticsVector.resize( numberOfTimeSteps );
m_MaskedImageStatisticsVector.resize( numberOfTimeSteps );
m_PlanarFigureStatisticsVector.resize( numberOfTimeSteps );
m_ImageStatisticsTimeStampVector.resize( numberOfTimeSteps );
m_MaskedImageStatisticsTimeStampVector.resize( numberOfTimeSteps );
m_PlanarFigureStatisticsTimeStampVector.resize( numberOfTimeSteps );
m_ImageStatisticsCalculationTriggerVector.resize( numberOfTimeSteps );
m_MaskedImageStatisticsCalculationTriggerVector.resize( numberOfTimeSteps );
m_PlanarFigureStatisticsCalculationTriggerVector.resize( numberOfTimeSteps );
for ( unsigned int t = 0; t < image->GetTimeSteps(); ++t )
{
m_ImageStatisticsTimeStampVector[t].Modified();
m_ImageStatisticsCalculationTriggerVector[t] = true;
}
}
}
void ImageStatisticsCalculator::SetImageMask( const mitk::Image *imageMask )
{
if ( m_Image.IsNull() )
{
itkExceptionMacro( << "Image needs to be set first!" );
}
if ( m_ImageMask != imageMask )
{
m_ImageMask = imageMask;
this->Modified();
for ( unsigned int t = 0; t < m_Image->GetTimeSteps(); ++t )
{
m_MaskedImageStatisticsTimeStampVector[t].Modified();
m_MaskedImageStatisticsCalculationTriggerVector[t] = true;
}
}
}
void ImageStatisticsCalculator::SetPlanarFigure( mitk::PlanarFigure *planarFigure )
{
if ( m_Image.IsNull() )
{
itkExceptionMacro( << "Image needs to be set first!" );
}
if ( m_PlanarFigure != planarFigure )
{
m_PlanarFigure = planarFigure;
this->Modified();
for ( unsigned int t = 0; t < m_Image->GetTimeSteps(); ++t )
{
m_PlanarFigureStatisticsTimeStampVector[t].Modified();
m_PlanarFigureStatisticsCalculationTriggerVector[t] = true;
}
}
}
void ImageStatisticsCalculator::SetMaskingMode( unsigned int mode )
{
if ( m_MaskingMode != mode )
{
m_MaskingMode = mode;
m_MaskingModeChanged = true;
this->Modified();
}
}
void ImageStatisticsCalculator::SetMaskingModeToNone()
{
if ( m_MaskingMode != MASKING_MODE_NONE )
{
m_MaskingMode = MASKING_MODE_NONE;
m_MaskingModeChanged = true;
this->Modified();
}
}
void ImageStatisticsCalculator::SetMaskingModeToImage()
{
if ( m_MaskingMode != MASKING_MODE_IMAGE )
{
m_MaskingMode = MASKING_MODE_IMAGE;
m_MaskingModeChanged = true;
this->Modified();
}
}
void ImageStatisticsCalculator::SetMaskingModeToPlanarFigure()
{
if ( m_MaskingMode != MASKING_MODE_PLANARFIGURE )
{
m_MaskingMode = MASKING_MODE_PLANARFIGURE;
m_MaskingModeChanged = true;
this->Modified();
}
}
void ImageStatisticsCalculator::SetIgnorePixelValue(double value)
{
if ( m_IgnorePixelValue != value )
{
m_IgnorePixelValue = value;
if(m_DoIgnorePixelValue)
{
m_IgnorePixelValueChanged = true;
}
this->Modified();
}
}
double ImageStatisticsCalculator::GetIgnorePixelValue()
{
return m_IgnorePixelValue;
}
void ImageStatisticsCalculator::SetDoIgnorePixelValue(bool value)
{
if ( m_DoIgnorePixelValue != value )
{
m_DoIgnorePixelValue = value;
m_IgnorePixelValueChanged = true;
this->Modified();
}
}
bool ImageStatisticsCalculator::GetDoIgnorePixelValue()
{
return m_DoIgnorePixelValue;
}
void ImageStatisticsCalculator::SetHistogramBinSize(unsigned int size)
{
this->m_HistogramBinSize = size;
}
unsigned int ImageStatisticsCalculator::GetHistogramBinSize()
{
return this->m_HistogramBinSize;
}
+
+void ImageStatisticsCalculator::SetHotspotRadiusInMM(double value)
+{
+ if ( m_HotspotRadiusInMM != value )
+ {
+ m_HotspotRadiusInMM = value;
+ if(m_CalculateHotspot)
+ {
+ m_HotspotRadiusInMMChanged = true;
+ //MITK_INFO <<"Hotspot radius changed, new convolution required";
+ }
+ this->Modified();
+ }
+}
+
+double ImageStatisticsCalculator::GetHotspotRadiusInMM()
+{
+ return m_HotspotRadiusInMM;
+}
+
+void ImageStatisticsCalculator::SetCalculateHotspot(bool on)
+{
+ if ( m_CalculateHotspot != on )
+ {
+ m_CalculateHotspot = on;
+ m_HotspotRadiusInMMChanged = true;
+ //MITK_INFO <<"Hotspot calculation changed, new convolution required";
+ this->Modified();
+ }
+}
+
+bool ImageStatisticsCalculator::IsHotspotCalculated()
+{
+ return m_CalculateHotspot;
+}
+
+void ImageStatisticsCalculator::SetHotspotMustBeCompletlyInsideImage(bool hotspotMustBeCompletelyInsideImage, bool warn)
+{
+ m_HotspotMustBeCompletelyInsideImage = hotspotMustBeCompletelyInsideImage;
+ if (!m_HotspotMustBeCompletelyInsideImage && warn)
+ {
+ MITK_WARN << "Hotspot calculation will extrapolate pixels at image borders. Be aware of the consequences for the hotspot location.";
+ }
+}
+
+bool ImageStatisticsCalculator::GetHotspotMustBeCompletlyInsideImage() const
+{
+ return m_HotspotMustBeCompletelyInsideImage;
+}
+
bool ImageStatisticsCalculator::ComputeStatistics( unsigned int timeStep )
{
if (m_Image.IsNull() )
{
mitkThrow() << "Image not set!";
}
if (!m_Image->IsInitialized())
{
mitkThrow() << "Image not initialized!";
}
if ( m_Image->GetReferenceCount() == 1 )
{
// Image no longer valid; we are the only ones to still hold a reference on it
return false;
}
if ( timeStep >= m_Image->GetTimeSteps() )
{
throw std::runtime_error( "Error: invalid time step!" );
}
// If a mask was set but we are the only ones to still hold a reference on
// it, delete it.
if ( m_ImageMask.IsNotNull() && (m_ImageMask->GetReferenceCount() == 1) )
{
m_ImageMask = NULL;
}
-
// Check if statistics is already up-to-date
unsigned long imageMTime = m_ImageStatisticsTimeStampVector[timeStep].GetMTime();
unsigned long maskedImageMTime = m_MaskedImageStatisticsTimeStampVector[timeStep].GetMTime();
unsigned long planarFigureMTime = m_PlanarFigureStatisticsTimeStampVector[timeStep].GetMTime();
bool imageStatisticsCalculationTrigger = m_ImageStatisticsCalculationTriggerVector[timeStep];
bool maskedImageStatisticsCalculationTrigger = m_MaskedImageStatisticsCalculationTriggerVector[timeStep];
bool planarFigureStatisticsCalculationTrigger = m_PlanarFigureStatisticsCalculationTriggerVector[timeStep];
if ( !m_IgnorePixelValueChanged
+ && !m_HotspotRadiusInMMChanged
&& ((m_MaskingMode != MASKING_MODE_NONE) || (imageMTime > m_Image->GetMTime() && !imageStatisticsCalculationTrigger))
&& ((m_MaskingMode != MASKING_MODE_IMAGE) || (maskedImageMTime > m_ImageMask->GetMTime() && !maskedImageStatisticsCalculationTrigger))
&& ((m_MaskingMode != MASKING_MODE_PLANARFIGURE) || (planarFigureMTime > m_PlanarFigure->GetMTime() && !planarFigureStatisticsCalculationTrigger)) )
{
// Statistics is up to date!
if ( m_MaskingModeChanged )
{
m_MaskingModeChanged = false;
- return true;
}
else
{
return false;
}
}
// Reset state changed flag
m_MaskingModeChanged = false;
m_IgnorePixelValueChanged = false;
// Depending on masking mode, extract and/or generate the required image
// and mask data from the user input
this->ExtractImageAndMask( timeStep );
StatisticsContainer *statisticsContainer;
HistogramContainer *histogramContainer;
switch ( m_MaskingMode )
{
case MASKING_MODE_NONE:
default:
if(!m_DoIgnorePixelValue)
{
statisticsContainer = &m_ImageStatisticsVector[timeStep];
histogramContainer = &m_ImageHistogramVector[timeStep];
m_ImageStatisticsTimeStampVector[timeStep].Modified();
m_ImageStatisticsCalculationTriggerVector[timeStep] = false;
}
else
{
statisticsContainer = &m_MaskedImageStatisticsVector[timeStep];
histogramContainer = &m_MaskedImageHistogramVector[timeStep];
m_MaskedImageStatisticsTimeStampVector[timeStep].Modified();
m_MaskedImageStatisticsCalculationTriggerVector[timeStep] = false;
}
break;
case MASKING_MODE_IMAGE:
statisticsContainer = &m_MaskedImageStatisticsVector[timeStep];
histogramContainer = &m_MaskedImageHistogramVector[timeStep];
m_MaskedImageStatisticsTimeStampVector[timeStep].Modified();
m_MaskedImageStatisticsCalculationTriggerVector[timeStep] = false;
break;
case MASKING_MODE_PLANARFIGURE:
statisticsContainer = &m_PlanarFigureStatisticsVector[timeStep];
histogramContainer = &m_PlanarFigureHistogramVector[timeStep];
m_PlanarFigureStatisticsTimeStampVector[timeStep].Modified();
m_PlanarFigureStatisticsCalculationTriggerVector[timeStep] = false;
break;
}
// Calculate statistics and histogram(s)
if ( m_InternalImage->GetDimension() == 3 )
{
if ( m_MaskingMode == MASKING_MODE_NONE && !m_DoIgnorePixelValue )
{
AccessFixedDimensionByItk_2(
m_InternalImage,
InternalCalculateStatisticsUnmasked,
3,
statisticsContainer,
histogramContainer );
}
else
{
AccessFixedDimensionByItk_3(
m_InternalImage,
InternalCalculateStatisticsMasked,
3,
m_InternalImageMask3D.GetPointer(),
statisticsContainer,
histogramContainer );
}
}
else if ( m_InternalImage->GetDimension() == 2 )
{
if ( m_MaskingMode == MASKING_MODE_NONE && !m_DoIgnorePixelValue )
{
AccessFixedDimensionByItk_2(
m_InternalImage,
InternalCalculateStatisticsUnmasked,
2,
statisticsContainer,
histogramContainer );
}
else
{
AccessFixedDimensionByItk_3(
m_InternalImage,
InternalCalculateStatisticsMasked,
2,
m_InternalImageMask2D.GetPointer(),
statisticsContainer,
histogramContainer );
}
}
else
{
MITK_ERROR << "ImageStatistics: Image dimension not supported!";
}
// Release unused image smart pointers to free memory
m_InternalImage = mitk::Image::ConstPointer();
m_InternalImageMask3D = MaskImage3DType::Pointer();
m_InternalImageMask2D = MaskImage2DType::Pointer();
return true;
}
const ImageStatisticsCalculator::HistogramType *
ImageStatisticsCalculator::GetHistogram( unsigned int timeStep, unsigned int label ) const
{
if ( m_Image.IsNull() || (timeStep >= m_Image->GetTimeSteps()) )
{
return NULL;
}
switch ( m_MaskingMode )
{
case MASKING_MODE_NONE:
default:
{
if(m_DoIgnorePixelValue)
return m_MaskedImageHistogramVector[timeStep][label];
return m_ImageHistogramVector[timeStep][label];
}
case MASKING_MODE_IMAGE:
return m_MaskedImageHistogramVector[timeStep][label];
case MASKING_MODE_PLANARFIGURE:
return m_PlanarFigureHistogramVector[timeStep][label];
}
}
const ImageStatisticsCalculator::HistogramContainer &
ImageStatisticsCalculator::GetHistogramVector( unsigned int timeStep ) const
{
if ( m_Image.IsNull() || (timeStep >= m_Image->GetTimeSteps()) )
{
return m_EmptyHistogramContainer;
}
switch ( m_MaskingMode )
{
case MASKING_MODE_NONE:
default:
{
if(m_DoIgnorePixelValue)
return m_MaskedImageHistogramVector[timeStep];
return m_ImageHistogramVector[timeStep];
}
case MASKING_MODE_IMAGE:
return m_MaskedImageHistogramVector[timeStep];
case MASKING_MODE_PLANARFIGURE:
return m_PlanarFigureHistogramVector[timeStep];
}
}
const ImageStatisticsCalculator::Statistics &
ImageStatisticsCalculator::GetStatistics( unsigned int timeStep, unsigned int label ) const
{
if ( m_Image.IsNull() || (timeStep >= m_Image->GetTimeSteps()) )
{
return m_EmptyStatistics;
}
switch ( m_MaskingMode )
{
case MASKING_MODE_NONE:
default:
{
if(m_DoIgnorePixelValue)
return m_MaskedImageStatisticsVector[timeStep][label];
return m_ImageStatisticsVector[timeStep][label];
}
case MASKING_MODE_IMAGE:
return m_MaskedImageStatisticsVector[timeStep][label];
case MASKING_MODE_PLANARFIGURE:
return m_PlanarFigureStatisticsVector[timeStep][label];
}
}
-
const ImageStatisticsCalculator::StatisticsContainer &
ImageStatisticsCalculator::GetStatisticsVector( unsigned int timeStep ) const
{
if ( m_Image.IsNull() || (timeStep >= m_Image->GetTimeSteps()) )
{
return m_EmptyStatisticsContainer;
}
switch ( m_MaskingMode )
{
case MASKING_MODE_NONE:
default:
{
if(m_DoIgnorePixelValue)
return m_MaskedImageStatisticsVector[timeStep];
return m_ImageStatisticsVector[timeStep];
}
case MASKING_MODE_IMAGE:
return m_MaskedImageStatisticsVector[timeStep];
case MASKING_MODE_PLANARFIGURE:
return m_PlanarFigureStatisticsVector[timeStep];
}
}
void ImageStatisticsCalculator::ExtractImageAndMask( unsigned int timeStep )
{
if ( m_Image.IsNull() )
{
throw std::runtime_error( "Error: image empty!" );
}
if ( timeStep >= m_Image->GetTimeSteps() )
{
throw std::runtime_error( "Error: invalid time step!" );
}
ImageTimeSelector::Pointer imageTimeSelector = ImageTimeSelector::New();
imageTimeSelector->SetInput( m_Image );
imageTimeSelector->SetTimeNr( timeStep );
imageTimeSelector->UpdateLargestPossibleRegion();
mitk::Image *timeSliceImage = imageTimeSelector->GetOutput();
switch ( m_MaskingMode )
{
case MASKING_MODE_NONE:
{
m_InternalImage = timeSliceImage;
m_InternalImageMask2D = NULL;
m_InternalImageMask3D = NULL;
if(m_DoIgnorePixelValue)
{
if( m_InternalImage->GetDimension() == 3 )
{
if(itk::ImageIOBase::USHORT != timeSliceImage->GetPixelType().GetComponentType())
CastToItkImage( timeSliceImage, m_InternalImageMask3D );
else
CastToItkImage( timeSliceImage->Clone(), m_InternalImageMask3D );
m_InternalImageMask3D->FillBuffer(1);
}
if( m_InternalImage->GetDimension() == 2 )
{
if(itk::ImageIOBase::USHORT != timeSliceImage->GetPixelType().GetComponentType())
CastToItkImage( timeSliceImage, m_InternalImageMask2D );
else
CastToItkImage( timeSliceImage->Clone(), m_InternalImageMask2D );
m_InternalImageMask2D->FillBuffer(1);
}
}
break;
}
case MASKING_MODE_IMAGE:
{
if ( m_ImageMask.IsNotNull() && (m_ImageMask->GetReferenceCount() > 1) )
{
if ( timeStep >= m_ImageMask->GetTimeSteps() )
{
// Use the last mask time step in case the current time step is bigger than the total
// number of mask time steps.
// It makes more sense setting this to the last mask time step than to 0.
// For instance if you have a mask with 2 time steps and an image with 5:
// If time step 0 is selected, the mask will use time step 0.
// If time step 1 is selected, the mask will use time step 1.
// If time step 2+ is selected, the mask will use time step 1.
// If you have a mask with only one time step instead, this will always default to 0.
timeStep = m_ImageMask->GetTimeSteps() - 1;
}
ImageTimeSelector::Pointer maskedImageTimeSelector = ImageTimeSelector::New();
maskedImageTimeSelector->SetInput( m_ImageMask );
maskedImageTimeSelector->SetTimeNr( timeStep );
maskedImageTimeSelector->UpdateLargestPossibleRegion();
mitk::Image *timeSliceMaskedImage = maskedImageTimeSelector->GetOutput();
m_InternalImage = timeSliceImage;
CastToItkImage( timeSliceMaskedImage, m_InternalImageMask3D );
}
else
{
throw std::runtime_error( "Error: image mask empty!" );
}
break;
}
case MASKING_MODE_PLANARFIGURE:
{
m_InternalImageMask2D = NULL;
if ( m_PlanarFigure.IsNull() )
{
throw std::runtime_error( "Error: planar figure empty!" );
}
if ( !m_PlanarFigure->IsClosed() )
{
throw std::runtime_error( "Masking not possible for non-closed figures" );
}
const BaseGeometry *imageGeometry = timeSliceImage->GetGeometry();
if ( imageGeometry == NULL )
{
throw std::runtime_error( "Image geometry invalid!" );
}
const PlaneGeometry *planarFigurePlaneGeometry = m_PlanarFigure->GetPlaneGeometry();
if ( planarFigurePlaneGeometry == NULL )
{
throw std::runtime_error( "Planar-Figure not yet initialized!" );
}
const PlaneGeometry *planarFigureGeometry =
dynamic_cast< const PlaneGeometry * >( planarFigurePlaneGeometry );
if ( planarFigureGeometry == NULL )
{
throw std::runtime_error( "Non-planar planar figures not supported!" );
}
// Find principal direction of PlanarFigure in input image
unsigned int axis;
if ( !this->GetPrincipalAxis( imageGeometry,
planarFigureGeometry->GetNormal(), axis ) )
{
throw std::runtime_error( "Non-aligned planar figures not supported!" );
}
m_PlanarFigureAxis = axis;
// Find slice number corresponding to PlanarFigure in input image
MaskImage3DType::IndexType index;
imageGeometry->WorldToIndex( planarFigureGeometry->GetOrigin(), index );
unsigned int slice = index[axis];
m_PlanarFigureSlice = slice;
// Extract slice with given position and direction from image
unsigned int dimension = timeSliceImage->GetDimension();
if (dimension != 2)
{
ExtractImageFilter::Pointer imageExtractor = ExtractImageFilter::New();
imageExtractor->SetInput( timeSliceImage );
imageExtractor->SetSliceDimension( axis );
imageExtractor->SetSliceIndex( slice );
imageExtractor->Update();
m_InternalImage = imageExtractor->GetOutput();
}
else
{
m_InternalImage = timeSliceImage;
}
// Compute mask from PlanarFigure
AccessFixedDimensionByItk_1(
m_InternalImage,
InternalCalculateMaskFromPlanarFigure,
2, axis );
}
}
if(m_DoIgnorePixelValue)
{
if ( m_InternalImage->GetDimension() == 3 )
{
AccessFixedDimensionByItk_1(
m_InternalImage,
InternalMaskIgnoredPixels,
3,
m_InternalImageMask3D.GetPointer() );
}
else if ( m_InternalImage->GetDimension() == 2 )
{
AccessFixedDimensionByItk_1(
m_InternalImage,
InternalMaskIgnoredPixels,
2,
m_InternalImageMask2D.GetPointer() );
}
}
}
bool ImageStatisticsCalculator::GetPrincipalAxis(
const BaseGeometry *geometry, Vector3D vector,
unsigned int &axis )
{
vector.Normalize();
for ( unsigned int i = 0; i < 3; ++i )
{
Vector3D axisVector = geometry->GetAxisVector( i );
axisVector.Normalize();
if ( fabs( fabs( axisVector * vector ) - 1.0) < mitk::eps )
{
axis = i;
return true;
}
}
return false;
}
template < typename TPixel, unsigned int VImageDimension >
void ImageStatisticsCalculator::InternalCalculateStatisticsUnmasked(
const itk::Image< TPixel, VImageDimension > *image,
StatisticsContainer *statisticsContainer,
HistogramContainer* histogramContainer )
{
typedef itk::Image< TPixel, VImageDimension > ImageType;
- typedef itk::Image< unsigned short, VImageDimension > MaskImageType;
typedef typename ImageType::IndexType IndexType;
typedef itk::Statistics::ScalarImageToHistogramGenerator< ImageType >
HistogramGeneratorType;
statisticsContainer->clear();
histogramContainer->clear();
// Progress listening...
typedef itk::SimpleMemberCommand< ImageStatisticsCalculator > ITKCommandType;
ITKCommandType::Pointer progressListener;
progressListener = ITKCommandType::New();
progressListener->SetCallbackFunction( this,
&ImageStatisticsCalculator::UnmaskedStatisticsProgressUpdate );
// Issue 100 artificial progress events since ScalarIMageToHistogramGenerator
// does not (yet?) support progress reporting
this->InvokeEvent( itk::StartEvent() );
for ( unsigned int i = 0; i < 100; ++i )
{
this->UnmaskedStatisticsProgressUpdate();
}
// Calculate statistics (separate filter)
typedef itk::StatisticsImageFilter< ImageType > StatisticsFilterType;
typename StatisticsFilterType::Pointer statisticsFilter = StatisticsFilterType::New();
statisticsFilter->SetInput( image );
+
unsigned long observerTag = statisticsFilter->AddObserver( itk::ProgressEvent(), progressListener );
statisticsFilter->Update();
statisticsFilter->RemoveObserver( observerTag );
this->InvokeEvent( itk::EndEvent() );
// Calculate minimum and maximum
typedef itk::MinimumMaximumImageCalculator< ImageType > MinMaxFilterType;
typename MinMaxFilterType::Pointer minMaxFilter = MinMaxFilterType::New();
minMaxFilter->SetImage( image );
unsigned long observerTag2 = minMaxFilter->AddObserver( itk::ProgressEvent(), progressListener );
minMaxFilter->Compute();
minMaxFilter->RemoveObserver( observerTag2 );
this->InvokeEvent( itk::EndEvent() );
Statistics statistics; statistics.Reset();
- statistics.Label = 1;
- statistics.N = image->GetBufferedRegion().GetNumberOfPixels();
- statistics.Min = statisticsFilter->GetMinimum();
- statistics.Max = statisticsFilter->GetMaximum();
- statistics.Mean = statisticsFilter->GetMean();
- statistics.Median = 0.0;
- statistics.Sigma = statisticsFilter->GetSigma();
- statistics.RMS = sqrt( statistics.Mean * statistics.Mean + statistics.Sigma * statistics.Sigma );
+ statistics.SetLabel(1);
+ statistics.SetN(image->GetBufferedRegion().GetNumberOfPixels());
+ statistics.SetMin(statisticsFilter->GetMinimum());
+ statistics.SetMax(statisticsFilter->GetMaximum());
+ statistics.SetMean(statisticsFilter->GetMean());
+ statistics.SetMedian(0.0);
+ statistics.SetVariance(statisticsFilter->GetVariance());
+ statistics.SetSigma(statisticsFilter->GetSigma());
+ statistics.SetRMS(sqrt( statistics.GetMean() * statistics.GetMean() + statistics.GetSigma() * statistics.GetSigma() ));
+
+ statistics.GetMinIndex().set_size(image->GetImageDimension());
+ statistics.GetMaxIndex().set_size(image->GetImageDimension());
+
+ vnl_vector tmpMaxIndex;
+ vnl_vector tmpMinIndex;
+
+ tmpMaxIndex.set_size(image->GetImageDimension() );
+ tmpMinIndex.set_size(image->GetImageDimension() );
+
+ for (unsigned int i=0; iGetIndexOfMaximum()[i];
+ tmpMinIndex[i] = minMaxFilter->GetIndexOfMinimum()[i];
+ }
- statistics.MinIndex.set_size(image->GetImageDimension());
- statistics.MaxIndex.set_size(image->GetImageDimension());
- for (unsigned int i=0; iGetIndexOfMaximum()[i];
- statistics.MinIndex[i] = minMaxFilter->GetIndexOfMinimum()[i];
+ typedef itk::Image< unsigned short, VImageDimension > MaskImageType;
+ typename MaskImageType::Pointer nullMask;
+ bool isHotspotDefined(false);
+ Statistics hotspotStatistics = this->CalculateHotspotStatistics(image, nullMask.GetPointer(), m_HotspotRadiusInMM, isHotspotDefined, 0 );
+ if (isHotspotDefined)
+ {
+ statistics.SetHasHotspotStatistics(true);
+ statistics.GetHotspotStatistics() = hotspotStatistics;
+ }
+ else
+ {
+ statistics.SetHasHotspotStatistics(false);
+ }
+
+ if(statistics.GetHotspotStatistics().HasHotspotStatistics() )
+ {
+ MITK_DEBUG << "Hotspot statistics available";
+ statistics.SetHotspotIndex(hotspotStatistics.GetHotspotIndex());
+ }
+ else
+ {
+ MITK_ERROR << "No hotspot statistics available!";
+ }
}
statisticsContainer->push_back( statistics );
// Calculate histogram
unsigned int numberOfBins = 200;
if (m_UseDefaultBinSize)
- m_HistogramBinSize = std::ceil( (statistics.Max - statistics.Min + 1)/numberOfBins );
+ m_HistogramBinSize = std::ceil( (statistics.GetMax() - statistics.GetMin() + 1)/numberOfBins );
else
- numberOfBins = std::floor( ( (statistics.Max - statistics.Min + 1) / m_HistogramBinSize) + 0.5 );
+ numberOfBins = std::floor( ( (statistics.GetMax() - statistics.GetMin() + 1) / m_HistogramBinSize) + 0.5 );
typename HistogramGeneratorType::Pointer histogramGenerator = HistogramGeneratorType::New();
histogramGenerator->SetInput( image );
histogramGenerator->SetMarginalScale( 100 );
histogramGenerator->SetNumberOfBins( numberOfBins );
- histogramGenerator->SetHistogramMin( statistics.Min );
- histogramGenerator->SetHistogramMax( statistics.Max );
+ histogramGenerator->SetHistogramMin( statistics.GetMin() );
+ histogramGenerator->SetHistogramMax( statistics.GetMax() );
histogramGenerator->Compute();
histogramContainer->push_back( histogramGenerator->GetOutput() );
}
template < typename TPixel, unsigned int VImageDimension >
void ImageStatisticsCalculator::InternalMaskIgnoredPixels(
const itk::Image< TPixel, VImageDimension > *image,
itk::Image< unsigned short, VImageDimension > *maskImage )
{
typedef itk::Image< TPixel, VImageDimension > ImageType;
typedef itk::Image< unsigned short, VImageDimension > MaskImageType;
itk::ImageRegionIterator
itmask(maskImage, maskImage->GetLargestPossibleRegion());
itk::ImageRegionConstIterator
itimage(image, image->GetLargestPossibleRegion());
itmask.GoToBegin();
itimage.GoToBegin();
while( !itmask.IsAtEnd() )
{
if(m_IgnorePixelValue == itimage.Get())
{
itmask.Set(0);
}
++itmask;
++itimage;
}
}
template < typename TPixel, unsigned int VImageDimension >
void ImageStatisticsCalculator::InternalCalculateStatisticsMasked(
const itk::Image< TPixel, VImageDimension > *image,
itk::Image< unsigned short, VImageDimension > *maskImage,
StatisticsContainer* statisticsContainer,
HistogramContainer* histogramContainer )
{
typedef itk::Image< TPixel, VImageDimension > ImageType;
typedef itk::Image< unsigned short, VImageDimension > MaskImageType;
typedef typename ImageType::IndexType IndexType;
typedef typename ImageType::PointType PointType;
typedef typename ImageType::SpacingType SpacingType;
typedef itk::LabelStatisticsImageFilter< ImageType, MaskImageType > LabelStatisticsFilterType;
typedef itk::ChangeInformationImageFilter< MaskImageType > ChangeInformationFilterType;
typedef itk::ExtractImageFilter< ImageType, ImageType > ExtractImageFilterType;
statisticsContainer->clear();
histogramContainer->clear();
-
// Make sure that mask is set
if ( maskImage == NULL )
{
itkExceptionMacro( << "Mask image needs to be set!" );
}
// Make sure that spacing of mask and image are the same
SpacingType imageSpacing = image->GetSpacing();
SpacingType maskSpacing = maskImage->GetSpacing();
PointType zeroPoint; zeroPoint.Fill( 0.0 );
if ( (zeroPoint + imageSpacing).SquaredEuclideanDistanceTo( (zeroPoint + maskSpacing) ) > mitk::eps )
{
itkExceptionMacro( << "Mask needs to have same spacing as image! (Image spacing: " << imageSpacing << "; Mask spacing: " << maskSpacing << ")" );
}
// Make sure that orientation of mask and image are the same
typedef typename ImageType::DirectionType DirectionType;
DirectionType imageDirection = image->GetDirection();
DirectionType maskDirection = maskImage->GetDirection();
for( int i = 0; i < imageDirection.ColumnDimensions; ++i )
{
for( int j = 0; j < imageDirection.ColumnDimensions; ++j )
{
double differenceDirection = imageDirection[i][j] - maskDirection[i][j];
if ( fabs( differenceDirection ) > mitk::eps )
{
itkExceptionMacro( << "Mask needs to have same direction as image! (Image direction: " << imageDirection << "; Mask direction: " << maskDirection << ")" );
}
}
}
// Make sure that the voxels of mask and image are correctly "aligned", i.e., voxel boundaries are the same in both images
PointType imageOrigin = image->GetOrigin();
PointType maskOrigin = maskImage->GetOrigin();
long offset[ImageType::ImageDimension];
typedef itk::ContinuousIndex ContinousIndexType;
ContinousIndexType maskOriginContinousIndex, imageOriginContinousIndex;
image->TransformPhysicalPointToContinuousIndex(maskOrigin, maskOriginContinousIndex);
image->TransformPhysicalPointToContinuousIndex(imageOrigin, imageOriginContinousIndex);
for ( unsigned int i = 0; i < ImageType::ImageDimension; ++i )
{
double misalignment = maskOriginContinousIndex[i] - floor( maskOriginContinousIndex[i] + 0.5 );
if ( fabs( misalignment ) > mitk::eps )
{
itkExceptionMacro( << "Pixels/voxels of mask and image are not sufficiently aligned! (Misalignment: " << misalignment << ")" );
}
double indexCoordDistance = maskOriginContinousIndex[i] - imageOriginContinousIndex[i];
- offset[i] = (int) indexCoordDistance + image->GetBufferedRegion().GetIndex()[i];
+ offset[i] = int( indexCoordDistance + image->GetBufferedRegion().GetIndex()[i] + 0.5 );
}
// Adapt the origin and region (index/size) of the mask so that the origin of both are the same
typename ChangeInformationFilterType::Pointer adaptMaskFilter;
adaptMaskFilter = ChangeInformationFilterType::New();
adaptMaskFilter->ChangeOriginOn();
adaptMaskFilter->ChangeRegionOn();
adaptMaskFilter->SetInput( maskImage );
adaptMaskFilter->SetOutputOrigin( image->GetOrigin() );
adaptMaskFilter->SetOutputOffset( offset );
adaptMaskFilter->Update();
typename MaskImageType::Pointer adaptedMaskImage = adaptMaskFilter->GetOutput();
-
// Make sure that mask region is contained within image region
if ( !image->GetLargestPossibleRegion().IsInside( adaptedMaskImage->GetLargestPossibleRegion() ) )
{
itkExceptionMacro( << "Mask region needs to be inside of image region! (Image region: "
<< image->GetLargestPossibleRegion() << "; Mask region: " << adaptedMaskImage->GetLargestPossibleRegion() << ")" );
}
// If mask region is smaller than image region, extract the sub-sampled region from the original image
typename ImageType::SizeType imageSize = image->GetBufferedRegion().GetSize();
typename ImageType::SizeType maskSize = maskImage->GetBufferedRegion().GetSize();
bool maskSmallerImage = false;
for ( unsigned int i = 0; i < ImageType::ImageDimension; ++i )
{
if ( maskSize[i] < imageSize[i] )
{
maskSmallerImage = true;
}
}
typename ImageType::ConstPointer adaptedImage;
if ( maskSmallerImage )
{
typename ExtractImageFilterType::Pointer extractImageFilter = ExtractImageFilterType::New();
extractImageFilter->SetInput( image );
extractImageFilter->SetExtractionRegion( adaptedMaskImage->GetBufferedRegion() );
extractImageFilter->Update();
adaptedImage = extractImageFilter->GetOutput();
}
else
{
adaptedImage = image;
}
// Initialize Filter
typedef itk::StatisticsImageFilter< ImageType > StatisticsFilterType;
typename StatisticsFilterType::Pointer statisticsFilter = StatisticsFilterType::New();
statisticsFilter->SetInput( adaptedImage );
statisticsFilter->Update();
int numberOfBins = std::floor( ( (statisticsFilter->GetMaximum() - statisticsFilter->GetMinimum() + 1) / m_HistogramBinSize) + 0.5 );
typename LabelStatisticsFilterType::Pointer labelStatisticsFilter;
labelStatisticsFilter = LabelStatisticsFilterType::New();
labelStatisticsFilter->SetInput( adaptedImage );
labelStatisticsFilter->SetLabelInput( adaptedMaskImage );
labelStatisticsFilter->UseHistogramsOn();
labelStatisticsFilter->SetHistogramParameters( numberOfBins, statisticsFilter->GetMinimum(), statisticsFilter->GetMaximum() );
// Add progress listening
typedef itk::SimpleMemberCommand< ImageStatisticsCalculator > ITKCommandType;
ITKCommandType::Pointer progressListener;
progressListener = ITKCommandType::New();
progressListener->SetCallbackFunction( this,
&ImageStatisticsCalculator::MaskedStatisticsProgressUpdate );
unsigned long observerTag = labelStatisticsFilter->AddObserver(
itk::ProgressEvent(), progressListener );
// Execute filter
this->InvokeEvent( itk::StartEvent() );
// Make sure that only the mask region is considered (otherwise, if the mask region is smaller
// than the image region, the Update() would result in an exception).
labelStatisticsFilter->GetOutput()->SetRequestedRegion( adaptedMaskImage->GetLargestPossibleRegion() );
// Execute the filter
labelStatisticsFilter->Update();
this->InvokeEvent( itk::EndEvent() );
labelStatisticsFilter->RemoveObserver( observerTag );
// Find all relevant labels of mask (other than 0)
std::list< int > relevantLabels;
bool maskNonEmpty = false;
unsigned int i;
for ( i = 1; i < 4096; ++i )
{
if ( labelStatisticsFilter->HasLabel( i ) )
{
relevantLabels.push_back( i );
maskNonEmpty = true;
}
}
+
if ( maskNonEmpty )
{
std::list< int >::iterator it;
for ( it = relevantLabels.begin(), i = 0;
- it != relevantLabels.end();
- ++it, ++i )
+ it != relevantLabels.end();
+ ++it, ++i )
{
+ Statistics statistics; // restore previous code
histogramContainer->push_back( HistogramType::ConstPointer( labelStatisticsFilter->GetHistogram( (*it) ) ) );
- Statistics statistics;
- statistics.Label = (*it);
- statistics.N = labelStatisticsFilter->GetCount( *it );
- statistics.Min = labelStatisticsFilter->GetMinimum( *it );
- statistics.Max = labelStatisticsFilter->GetMaximum( *it );
- statistics.Mean = labelStatisticsFilter->GetMean( *it );
- statistics.Median = labelStatisticsFilter->GetMedian( *it );
- statistics.Sigma = labelStatisticsFilter->GetSigma( *it );
- statistics.RMS = sqrt( statistics.Mean * statistics.Mean
- + statistics.Sigma * statistics.Sigma );
+ statistics.SetLabel (*it);
+ statistics.SetN(labelStatisticsFilter->GetCount( *it ));
+ statistics.SetMin(labelStatisticsFilter->GetMinimum( *it ));
+ statistics.SetMax(labelStatisticsFilter->GetMaximum( *it ));
+ statistics.SetMean(labelStatisticsFilter->GetMean( *it ));
+ statistics.SetMedian(labelStatisticsFilter->GetMedian( *it ));
+ statistics.SetVariance(labelStatisticsFilter->GetVariance( *it ));
+ statistics.SetSigma(labelStatisticsFilter->GetSigma( *it ));
+ statistics.SetRMS(sqrt( statistics.GetMean() * statistics.GetMean()
+ + statistics.GetSigma() * statistics.GetSigma() ));
// restrict image to mask area for min/max index calculation
typedef itk::MaskImageFilter< ImageType, MaskImageType, ImageType > MaskImageFilterType;
typename MaskImageFilterType::Pointer masker = MaskImageFilterType::New();
- bool isMinAndMaxSameValue = (statistics.Min == statistics.Max);
+ bool isMinAndMaxSameValue = (statistics.GetMin() == statistics.GetMax());
// bug 17962: following is a workaround for the case when min and max are the same, we can probably find a nicer way here
- double outsideValue = (isMinAndMaxSameValue ? (statistics.Max/2) : (statistics.Min+statistics.Max)/2);
+ double outsideValue = (isMinAndMaxSameValue ? (statistics.GetMax()/2) : (statistics.GetMin()+statistics.GetMax())/2);
masker->SetOutsideValue( outsideValue );
masker->SetInput1(adaptedImage);
masker->SetInput2(adaptedMaskImage);
masker->Update();
// get index of minimum and maximum
typedef itk::MinimumMaximumImageCalculator< ImageType > MinMaxFilterType;
typename MinMaxFilterType::Pointer minMaxFilter = MinMaxFilterType::New();
minMaxFilter->SetImage( masker->GetOutput() );
unsigned long observerTag2 = minMaxFilter->AddObserver( itk::ProgressEvent(), progressListener );
minMaxFilter->Compute();
minMaxFilter->RemoveObserver( observerTag2 );
this->InvokeEvent( itk::EndEvent() );
- statistics.MinIndex.set_size(adaptedImage->GetImageDimension());
- statistics.MaxIndex.set_size(adaptedImage->GetImageDimension());
- typename MinMaxFilterType::IndexType tempMaxIndex = minMaxFilter->GetIndexOfMaximum();
- // bug 17962: following is a workaround for the case when min and max are the same, we can probably find a nicer way here
- typename MinMaxFilterType::IndexType tempMinIndex =
- (isMinAndMaxSameValue ? minMaxFilter->GetIndexOfMaximum() : minMaxFilter->GetIndexOfMinimum());
+ typename MinMaxFilterType::IndexType tempMaxIndex = minMaxFilter->GetIndexOfMaximum();
+ // bug 17962: following is a workaround for the case when min and max are the same, we can probably find a nicer way here
+ typename MinMaxFilterType::IndexType tempMinIndex =
+ (isMinAndMaxSameValue ? minMaxFilter->GetIndexOfMaximum() : minMaxFilter->GetIndexOfMinimum());
-// FIX BUG 14644
- //If a PlanarFigure is used for segmentation the
- //adaptedImage is a single slice (2D). Adding the
- // 3. dimension.
- if (m_MaskingMode == MASKING_MODE_PLANARFIGURE && m_Image->GetDimension()==3)
- {
- statistics.MaxIndex.set_size(m_Image->GetDimension());
- statistics.MaxIndex[m_PlanarFigureCoordinate0]=tempMaxIndex[0];
- statistics.MaxIndex[m_PlanarFigureCoordinate1]=tempMaxIndex[1];
- statistics.MaxIndex[m_PlanarFigureAxis]=m_PlanarFigureSlice;
-
- statistics.MinIndex.set_size(m_Image->GetDimension());
- statistics.MinIndex[m_PlanarFigureCoordinate0]=tempMinIndex[0];
- statistics.MinIndex[m_PlanarFigureCoordinate1]=tempMinIndex[1];
- statistics.MinIndex[m_PlanarFigureAxis]=m_PlanarFigureSlice;
- } else
+ // FIX BUG 14644
+ //If a PlanarFigure is used for segmentation the
+ //adaptedImage is a single slice (2D). Adding the
+ // 3. dimension.
+
+ vnl_vector maxIndex;
+ vnl_vector minIndex;
+ maxIndex.set_size(m_Image->GetDimension());
+ minIndex.set_size(m_Image->GetDimension());
+
+ if (m_MaskingMode == MASKING_MODE_PLANARFIGURE && m_Image->GetDimension()==3)
+ {
+ maxIndex[m_PlanarFigureCoordinate0] = tempMaxIndex[0];
+ maxIndex[m_PlanarFigureCoordinate1] = tempMaxIndex[1];
+ maxIndex[m_PlanarFigureAxis] = m_PlanarFigureSlice;
+
+ minIndex[m_PlanarFigureCoordinate0] = tempMinIndex[0] ;
+ minIndex[m_PlanarFigureCoordinate1] = tempMinIndex[1];
+ minIndex[m_PlanarFigureAxis] = m_PlanarFigureSlice;
+ } else
+ {
+ for (unsigned int i = 0; ipush_back( statistics );
}
}
else
{
histogramContainer->push_back( HistogramType::ConstPointer( m_EmptyHistogram ) );
statisticsContainer->push_back( Statistics() );
}
}
+template
+ImageStatisticsCalculator::ImageExtrema
+ImageStatisticsCalculator::CalculateExtremaWorld(
+ const itk::Image *inputImage,
+ itk::Image *maskImage,
+ double neccessaryDistanceToImageBorderInMM,
+ unsigned int label)
+{
+ typedef itk::Image< TPixel, VImageDimension > ImageType;
+ typedef itk::Image< unsigned short, VImageDimension > MaskImageType;
+
+ typedef itk::ImageRegionConstIteratorWithIndex MaskImageIteratorType;
+ typedef itk::ImageRegionConstIteratorWithIndex InputImageIndexIteratorType;
+
+ typename ImageType::SpacingType spacing = inputImage->GetSpacing();
+
+ ImageExtrema minMax;
+ minMax.Defined = false;
+ minMax.MaxIndex.set_size(VImageDimension);
+ minMax.MaxIndex.set_size(VImageDimension);
+
+ typename ImageType::RegionType allowedExtremaRegion = inputImage->GetLargestPossibleRegion();
+
+ bool keepDistanceToImageBorders( neccessaryDistanceToImageBorderInMM > 0 );
+ if (keepDistanceToImageBorders)
+ {
+ long distanceInPixels[VImageDimension];
+ for(unsigned short dimension = 0; dimension < VImageDimension; ++dimension)
+ {
+ // To confirm that the whole hotspot is inside the image we have to keep a specific distance to the image-borders, which is as long as
+ // the radius. To get the amount of indices we divide the radius by spacing and add 0.5 because voxels are center based:
+ // For example with a radius of 2.2 and a spacing of 1 two indices are enough because 2.2 / 1 + 0.5 = 2.7 => 2.
+ // But with a radius of 2.7 we need 3 indices because 2.7 / 1 + 0.5 = 3.2 => 3
+ distanceInPixels[dimension] = int( neccessaryDistanceToImageBorderInMM / spacing[dimension] + 0.5);
+ }
+
+ allowedExtremaRegion.ShrinkByRadius(distanceInPixels);
+ }
+
+ InputImageIndexIteratorType imageIndexIt(inputImage, allowedExtremaRegion);
+
+ float maxValue = itk::NumericTraits::min();
+ float minValue = itk::NumericTraits::max();
+
+ typename ImageType::IndexType maxIndex;
+ typename ImageType::IndexType minIndex;
+
+ for(unsigned short i = 0; i < VImageDimension; ++i)
+ {
+ maxIndex[i] = 0;
+ minIndex[i] = 0;
+ }
+
+ if (maskImage != NULL)
+ {
+ MaskImageIteratorType maskIt(maskImage, maskImage->GetLargestPossibleRegion());
+ typename ImageType::IndexType imageIndex;
+ typename ImageType::PointType worldPosition;
+ typename ImageType::IndexType maskIndex;
+
+ for(maskIt.GoToBegin(); !maskIt.IsAtEnd(); ++maskIt)
+ {
+ imageIndex = maskIndex = maskIt.GetIndex();
+
+ if(maskIt.Get() == label)
+ {
+ if( allowedExtremaRegion.IsInside(imageIndex) )
+ {
+ imageIndexIt.SetIndex( imageIndex );
+ double value = imageIndexIt.Get();
+ minMax.Defined = true;
+
+ //Calculate minimum, maximum and corresponding index-values
+ if( value > maxValue )
+ {
+ maxIndex = imageIndexIt.GetIndex();
+ maxValue = value;
+ }
+
+ if(value < minValue )
+ {
+ minIndex = imageIndexIt.GetIndex();
+ minValue = value;
+ }
+ }
+ }
+ }
+ }
+ else
+ {
+ for(imageIndexIt.GoToBegin(); !imageIndexIt.IsAtEnd(); ++imageIndexIt)
+ {
+ double value = imageIndexIt.Get();
+ minMax.Defined = true;
+
+ //Calculate minimum, maximum and corresponding index-values
+ if( value > maxValue )
+ {
+ maxIndex = imageIndexIt.GetIndex();
+ maxValue = value;
+ }
+
+ if(value < minValue )
+ {
+ minIndex = imageIndexIt.GetIndex();
+ minValue = value;
+ }
+ }
+ }
+
+ minMax.MaxIndex.set_size(VImageDimension);
+ minMax.MinIndex.set_size(VImageDimension);
+
+ for(unsigned int i = 0; i < minMax.MaxIndex.size(); ++i)
+ {
+ minMax.MaxIndex[i] = maxIndex[i];
+ }
+
+ for(unsigned int i = 0; i < minMax.MinIndex.size(); ++i)
+ {
+ minMax.MinIndex[i] = minIndex[i];
+ }
+
+ minMax.Max = maxValue;
+ minMax.Min = minValue;
+
+ return minMax;
+}
+
+template
+itk::Size
+ImageStatisticsCalculator
+::CalculateConvolutionKernelSize(double spacing[VImageDimension], double radiusInMM)
+{
+ typedef itk::Image< float, VImageDimension > KernelImageType;
+ typedef typename KernelImageType::SizeType SizeType;
+ SizeType maskSize;
+
+ for(unsigned int i = 0; i < VImageDimension; ++i)
+ {
+ maskSize[i] = static_cast( 2 * radiusInMM / spacing[i]);
+
+ // We always want an uneven size to have a clear center point in the convolution mask
+ if(maskSize[i] % 2 == 0 )
+ {
+ ++maskSize[i];
+ }
+ }
+ return maskSize;
+}
+
+template
+itk::SmartPointer< itk::Image >
+ImageStatisticsCalculator
+::GenerateHotspotSearchConvolutionKernel(double mmPerPixel[VImageDimension], double radiusInMM)
+{
+ std::stringstream ss;
+ for (unsigned int i = 0; i < VImageDimension; ++i)
+ {
+ ss << mmPerPixel[i];
+ if (i < VImageDimension -1)
+ ss << ",";
+ }
+ MITK_DEBUG << "Update convolution kernel for spacing (" << ss.str() << ") and radius " << radiusInMM << "mm";
+
+
+ double radiusInMMSquared = radiusInMM * radiusInMM;
+ typedef itk::Image< float, VImageDimension > KernelImageType;
+ typename KernelImageType::Pointer convolutionKernel = KernelImageType::New();
+
+ // Calculate size and allocate mask image
+ typedef typename KernelImageType::SizeType SizeType;
+ SizeType maskSize = this->CalculateConvolutionKernelSize(mmPerPixel, radiusInMM);
+
+ Point3D convolutionMaskCenterIndex; convolutionMaskCenterIndex.Fill(0.0);
+ for(unsigned int i = 0; i < VImageDimension; ++i)
+ {
+ convolutionMaskCenterIndex[i] = 0.5 * (double)(maskSize[i]-1);
+ }
+
+ typedef typename KernelImageType::IndexType IndexType;
+ IndexType maskIndex;
+ maskIndex.Fill(0);
+
+ typedef typename KernelImageType::RegionType RegionType;
+ RegionType maskRegion;
+ maskRegion.SetSize(maskSize);
+ maskRegion.SetIndex(maskIndex);
+
+ convolutionKernel->SetRegions(maskRegion);
+ convolutionKernel->SetSpacing(mmPerPixel);
+ convolutionKernel->Allocate();
+
+ // Fill mask image values by subsampling the image grid
+ typedef itk::ImageRegionIteratorWithIndex MaskIteratorType;
+ MaskIteratorType maskIt(convolutionKernel,maskRegion);
+
+ int numberOfSubVoxelsPerDimension = 2; // per dimension!
+ int numberOfSubVoxels = ::pow( static_cast(numberOfSubVoxelsPerDimension), static_cast(VImageDimension) );
+ double subVoxelSizeInPixels = 1.0 / (double)numberOfSubVoxelsPerDimension;
+ double valueOfOneSubVoxel = 1.0 / (double)numberOfSubVoxels;
+ double maskValue = 0.0;
+ Point3D subVoxelIndexPosition;
+ double distanceSquared = 0.0;
+
+ typedef itk::ContinuousIndex ContinuousIndexType;
+ for(maskIt.GoToBegin(); !maskIt.IsAtEnd(); ++maskIt)
+ {
+ ContinuousIndexType indexPoint(maskIt.GetIndex());
+ Point3D voxelPosition;
+ for (unsigned int dimension = 0; dimension < VImageDimension; ++dimension)
+ {
+ voxelPosition[dimension] = indexPoint[dimension];
+ }
+
+ maskValue = 0.0;
+ Vector3D subVoxelOffset; subVoxelOffset.Fill(0.0);
+ // iterate sub-voxels by iterating all possible offsets
+ for (subVoxelOffset[0] = -0.5 + subVoxelSizeInPixels / 2.0;
+ subVoxelOffset[0] < +0.5;
+ subVoxelOffset[0] += subVoxelSizeInPixels)
+ {
+ for (subVoxelOffset[1] = -0.5 + subVoxelSizeInPixels / 2.0;
+ subVoxelOffset[1] < +0.5;
+ subVoxelOffset[1] += subVoxelSizeInPixels)
+ {
+ for (subVoxelOffset[2] = -0.5 + subVoxelSizeInPixels / 2.0;
+ subVoxelOffset[2] < +0.5;
+ subVoxelOffset[2] += subVoxelSizeInPixels)
+ {
+ subVoxelIndexPosition = voxelPosition + subVoxelOffset; // this COULD be integrated into the for-loops if neccessary (add voxelPosition to initializer and end condition)
+ distanceSquared =
+ (subVoxelIndexPosition[0]-convolutionMaskCenterIndex[0]) * mmPerPixel[0] * (subVoxelIndexPosition[0]-convolutionMaskCenterIndex[0]) * mmPerPixel[0]
+ + (subVoxelIndexPosition[1]-convolutionMaskCenterIndex[1]) * mmPerPixel[1] * (subVoxelIndexPosition[1]-convolutionMaskCenterIndex[1]) * mmPerPixel[1]
+ + (subVoxelIndexPosition[2]-convolutionMaskCenterIndex[2]) * mmPerPixel[2] * (subVoxelIndexPosition[2]-convolutionMaskCenterIndex[2]) * mmPerPixel[2];
+
+ if (distanceSquared <= radiusInMMSquared)
+ {
+ maskValue += valueOfOneSubVoxel;
+ }
+ }
+ }
+ }
+ maskIt.Set( maskValue );
+ }
+
+ return convolutionKernel;
+}
+
+template
+itk::SmartPointer >
+ImageStatisticsCalculator::GenerateConvolutionImage( const itk::Image* inputImage )
+{
+ double mmPerPixel[VImageDimension];
+ for (unsigned int dimension = 0; dimension < VImageDimension; ++dimension)
+ {
+ mmPerPixel[dimension] = inputImage->GetSpacing()[dimension];
+ }
+
+ // update convolution kernel
+ typedef itk::Image< float, VImageDimension > KernelImageType;
+ typename KernelImageType::Pointer convolutionKernel = this->GenerateHotspotSearchConvolutionKernel(mmPerPixel, m_HotspotRadiusInMM);
+
+ // update convolution image
+ typedef itk::Image< TPixel, VImageDimension > InputImageType;
+ typedef itk::Image< TPixel, VImageDimension > ConvolutionImageType;
+ typedef itk::FFTConvolutionImageFilter ConvolutionFilterType;
+
+ typename ConvolutionFilterType::Pointer convolutionFilter = ConvolutionFilterType::New();
+ typedef itk::ConstantBoundaryCondition BoundaryConditionType;
+ BoundaryConditionType boundaryCondition;
+ boundaryCondition.SetConstant(0.0);
+
+ if (GetHotspotMustBeCompletlyInsideImage())
+ {
+ // overwrite default boundary condition
+ convolutionFilter->SetBoundaryCondition(&boundaryCondition);
+ }
+
+ convolutionFilter->SetInput(inputImage);
+ convolutionFilter->SetKernelImage(convolutionKernel);
+ convolutionFilter->SetNormalize(true);
+ MITK_DEBUG << "Update Convolution image for hotspot search";
+ convolutionFilter->UpdateLargestPossibleRegion();
+
+ typename ConvolutionImageType::Pointer convolutionImage = convolutionFilter->GetOutput();
+ convolutionImage->SetSpacing( inputImage->GetSpacing() ); // only workaround because convolution filter seems to ignore spacing of input image
+
+ m_HotspotRadiusInMMChanged = false;
+ return convolutionImage;
+}
+
+template < typename TPixel, unsigned int VImageDimension>
+void
+ImageStatisticsCalculator
+::FillHotspotMaskPixels( itk::Image* maskImage,
+ itk::Point sphereCenter,
+ double sphereRadiusInMM)
+{
+ typedef itk::Image< TPixel, VImageDimension > MaskImageType;
+ typedef itk::ImageRegionIteratorWithIndex MaskImageIteratorType;
+
+ MaskImageIteratorType maskIt(maskImage, maskImage->GetLargestPossibleRegion());
+
+ typename MaskImageType::IndexType maskIndex;
+ typename MaskImageType::PointType worldPosition;
+
+ for(maskIt.GoToBegin(); !maskIt.IsAtEnd(); ++maskIt)
+ {
+ maskIndex = maskIt.GetIndex();
+ maskImage->TransformIndexToPhysicalPoint(maskIndex, worldPosition);
+ maskIt.Set( worldPosition.EuclideanDistanceTo(sphereCenter) <= sphereRadiusInMM ? 1 : 0 );
+ }
+}
+
+template < typename TPixel, unsigned int VImageDimension>
+ImageStatisticsCalculator::Statistics
+ImageStatisticsCalculator::CalculateHotspotStatistics(
+ const itk::Image* inputImage,
+ itk::Image* maskImage,
+ double radiusInMM,
+ bool& isHotspotDefined,
+ unsigned int label)
+{
+ // get convolution image (updated in GenerateConvolutionImage())
+ typedef itk::Image< TPixel, VImageDimension > InputImageType;
+ typedef itk::Image< TPixel, VImageDimension > ConvolutionImageType;
+ typedef itk::Image< float, VImageDimension > KernelImageType;
+ typedef itk::Image< unsigned short, VImageDimension > MaskImageType;
+
+ //typename ConvolutionImageType::Pointer convolutionImage = dynamic_cast(this->GenerateConvolutionImage(inputImage));
+ typename ConvolutionImageType::Pointer convolutionImage = this->GenerateConvolutionImage(inputImage);
+
+ if (convolutionImage.IsNull())
+ {
+ MITK_ERROR << "Empty convolution image in CalculateHotspotStatistics(). We should never reach this state (logic error).";
+ throw std::logic_error("Empty convolution image in CalculateHotspotStatistics()");
+ }
+
+ // find maximum in convolution image, given the current mask
+ double requiredDistanceToBorder = m_HotspotMustBeCompletelyInsideImage ? m_HotspotRadiusInMM : -1.0;
+ ImageExtrema convolutionImageInformation = CalculateExtremaWorld(convolutionImage.GetPointer(), maskImage, requiredDistanceToBorder, label);
+
+ isHotspotDefined = convolutionImageInformation.Defined;
+
+ if (!isHotspotDefined)
+ {
+ m_EmptyStatistics.Reset(VImageDimension);
+ MITK_ERROR << "No origin of hotspot-sphere was calculated! Returning empty statistics";
+ return m_EmptyStatistics;
+ }
+ else
+ {
+ // create a binary mask around the "hotspot" region, fill the shape of a sphere around our hotspot center
+ typedef itk::ImageDuplicator< InputImageType > DuplicatorType;
+ typename DuplicatorType::Pointer copyMachine = DuplicatorType::New();
+ copyMachine->SetInputImage(inputImage);
+ copyMachine->Update();
+
+ typedef itk::CastImageFilter< InputImageType, MaskImageType > CastFilterType;
+ typename CastFilterType::Pointer caster = CastFilterType::New();
+ caster->SetInput( copyMachine->GetOutput() );
+ caster->Update();
+ typename MaskImageType::Pointer hotspotMaskITK = caster->GetOutput();
+
+ typedef typename InputImageType::IndexType IndexType;
+ IndexType maskCenterIndex;
+ for (unsigned int d =0; d< VImageDimension;++d) maskCenterIndex[d]=convolutionImageInformation.MaxIndex[d];
+ typename ConvolutionImageType::PointType maskCenter;
+ inputImage->TransformIndexToPhysicalPoint(maskCenterIndex,maskCenter);
+
+ this->FillHotspotMaskPixels(hotspotMaskITK.GetPointer(), maskCenter, radiusInMM);
+
+ // calculate statistics within the binary mask
+ typedef itk::LabelStatisticsImageFilter< InputImageType, MaskImageType> LabelStatisticsFilterType;
+ typename LabelStatisticsFilterType::Pointer labelStatisticsFilter;
+ labelStatisticsFilter = LabelStatisticsFilterType::New();
+ labelStatisticsFilter->SetInput( inputImage );
+ labelStatisticsFilter->SetLabelInput( hotspotMaskITK );
+ labelStatisticsFilter->Update();
+
+ Statistics hotspotStatistics;
+ hotspotStatistics.SetHotspotIndex(convolutionImageInformation.MaxIndex);
+ hotspotStatistics.SetMean(convolutionImageInformation.Max);
+
+ if ( labelStatisticsFilter->HasLabel( 1 ) )
+ {
+ hotspotStatistics.SetLabel (1);
+ hotspotStatistics.SetN(labelStatisticsFilter->GetCount(1));
+ hotspotStatistics.SetMin(labelStatisticsFilter->GetMinimum(1));
+ hotspotStatistics.SetMax(labelStatisticsFilter->GetMaximum(1));
+ hotspotStatistics.SetMedian(labelStatisticsFilter->GetMedian(1));
+ hotspotStatistics.SetVariance(labelStatisticsFilter->GetVariance(1));
+ hotspotStatistics.SetSigma(labelStatisticsFilter->GetSigma(1));
+ hotspotStatistics.SetRMS(sqrt( hotspotStatistics.GetMean() * hotspotStatistics.GetMean()
+ + hotspotStatistics.GetSigma() * hotspotStatistics.GetSigma() ));
+
+ MITK_DEBUG << "Statistics for inside hotspot: Mean " << hotspotStatistics.GetMean()
+ << ", SD " << hotspotStatistics.GetSigma()
+ << ", Max " << hotspotStatistics.GetMax()
+ << ", Min " << hotspotStatistics.GetMin();
+ }
+ else
+ {
+ MITK_ERROR << "Uh oh! Unable to calculate statistics for hotspot region...";
+ return m_EmptyStatistics;
+ }
+
+ return hotspotStatistics;
+ }
+}
template < typename TPixel, unsigned int VImageDimension >
void ImageStatisticsCalculator::InternalCalculateMaskFromPlanarFigure(
const itk::Image< TPixel, VImageDimension > *image, unsigned int axis )
{
typedef itk::Image< TPixel, VImageDimension > ImageType;
typedef itk::CastImageFilter< ImageType, MaskImage2DType > CastFilterType;
// Generate mask image as new image with same header as input image and
- // initialize with "1".
+ // initialize with 1.
typename CastFilterType::Pointer castFilter = CastFilterType::New();
castFilter->SetInput( image );
castFilter->Update();
castFilter->GetOutput()->FillBuffer( 1 );
// all PolylinePoints of the PlanarFigure are stored in a vtkPoints object.
// These points are used by the vtkLassoStencilSource to create
// a vtkImageStencil.
const mitk::PlaneGeometry *planarFigurePlaneGeometry = m_PlanarFigure->GetPlaneGeometry();
const typename PlanarFigure::PolyLineType planarFigurePolyline = m_PlanarFigure->GetPolyLine( 0 );
const mitk::BaseGeometry *imageGeometry3D = m_Image->GetGeometry( 0 );
// If there is a second poly line in a closed planar figure, treat it as a hole.
PlanarFigure::PolyLineType planarFigureHolePolyline;
if (m_PlanarFigure->GetPolyLinesSize() == 2)
planarFigureHolePolyline = m_PlanarFigure->GetPolyLine(1);
// Determine x- and y-dimensions depending on principal axis
int i0, i1;
switch ( axis )
{
case 0:
i0 = 1;
i1 = 2;
break;
case 1:
i0 = 0;
i1 = 2;
break;
case 2:
default:
i0 = 0;
i1 = 1;
break;
}
m_PlanarFigureCoordinate0= i0;
m_PlanarFigureCoordinate1= i1;
// store the polyline contour as vtkPoints object
bool outOfBounds = false;
vtkSmartPointer points = vtkSmartPointer::New();
typename PlanarFigure::PolyLineType::const_iterator it;
for ( it = planarFigurePolyline.begin();
it != planarFigurePolyline.end();
++it )
{
Point3D point3D;
// Convert 2D point back to the local index coordinates of the selected
// image
planarFigurePlaneGeometry->Map( *it, point3D );
// Polygons (partially) outside of the image bounds can not be processed
// further due to a bug in vtkPolyDataToImageStencil
if ( !imageGeometry3D->IsInside( point3D ) )
{
outOfBounds = true;
}
imageGeometry3D->WorldToIndex( point3D, point3D );
points->InsertNextPoint( point3D[i0], point3D[i1], 0 );
}
vtkSmartPointer holePoints = NULL;
if (!planarFigureHolePolyline.empty())
{
holePoints = vtkSmartPointer::New();
Point3D point3D;
PlanarFigure::PolyLineType::const_iterator end = planarFigureHolePolyline.end();
for (it = planarFigureHolePolyline.begin(); it != end; ++it)
{
planarFigurePlaneGeometry->Map(*it, point3D);
imageGeometry3D->WorldToIndex(point3D, point3D);
holePoints->InsertNextPoint(point3D[i0], point3D[i1], 0);
}
}
// mark a malformed 2D planar figure ( i.e. area = 0 ) as out of bounds
// this can happen when all control points of a rectangle lie on the same line = two of the three extents are zero
double bounds[6] = {0, 0, 0, 0, 0, 0};
points->GetBounds( bounds );
bool extent_x = (fabs(bounds[0] - bounds[1])) < mitk::eps;
bool extent_y = (fabs(bounds[2] - bounds[3])) < mitk::eps;
bool extent_z = (fabs(bounds[4] - bounds[5])) < mitk::eps;
// throw an exception if a closed planar figure is deformed, i.e. has only one non-zero extent
if ( m_PlanarFigure->IsClosed() &&
((extent_x && extent_y) || (extent_x && extent_z) || (extent_y && extent_z)))
{
mitkThrow() << "Figure has a zero area and cannot be used for masking.";
}
if ( outOfBounds )
{
throw std::runtime_error( "Figure at least partially outside of image bounds!" );
}
// create a vtkLassoStencilSource and set the points of the Polygon
vtkSmartPointer lassoStencil = vtkSmartPointer::New();
lassoStencil->SetShapeToPolygon();
lassoStencil->SetPoints( points );
vtkSmartPointer holeLassoStencil = NULL;
if (holePoints.GetPointer() != NULL)
{
holeLassoStencil = vtkSmartPointer::New();
holeLassoStencil->SetShapeToPolygon();
holeLassoStencil->SetPoints(holePoints);
}
// Export from ITK to VTK (to use a VTK filter)
typedef itk::VTKImageImport< MaskImage2DType > ImageImportType;
typedef itk::VTKImageExport< MaskImage2DType > ImageExportType;
typename ImageExportType::Pointer itkExporter = ImageExportType::New();
itkExporter->SetInput( castFilter->GetOutput() );
vtkSmartPointer vtkImporter = vtkSmartPointer::New();
this->ConnectPipelines( itkExporter, vtkImporter );
// Apply the generated image stencil to the input image
vtkSmartPointer imageStencilFilter = vtkSmartPointer::New();
imageStencilFilter->SetInputConnection( vtkImporter->GetOutputPort() );
imageStencilFilter->SetStencilConnection(lassoStencil->GetOutputPort());
imageStencilFilter->ReverseStencilOff();
imageStencilFilter->SetBackgroundValue( 0 );
imageStencilFilter->Update();
vtkSmartPointer holeStencilFilter = NULL;
if (holeLassoStencil.GetPointer() != NULL)
{
holeStencilFilter = vtkSmartPointer::New();
holeStencilFilter->SetInputConnection(imageStencilFilter->GetOutputPort());
holeStencilFilter->SetStencilConnection(holeLassoStencil->GetOutputPort());
holeStencilFilter->ReverseStencilOn();
holeStencilFilter->SetBackgroundValue(0);
holeStencilFilter->Update();
}
// Export from VTK back to ITK
vtkSmartPointer vtkExporter = vtkSmartPointer::New();
vtkExporter->SetInputConnection( holeStencilFilter.GetPointer() == NULL
? imageStencilFilter->GetOutputPort()
: holeStencilFilter->GetOutputPort());
vtkExporter->Update();
typename ImageImportType::Pointer itkImporter = ImageImportType::New();
this->ConnectPipelines( vtkExporter, itkImporter );
itkImporter->Update();
typedef itk::ImageDuplicator< ImageImportType::OutputImageType > DuplicatorType;
DuplicatorType::Pointer duplicator = DuplicatorType::New();
duplicator->SetInputImage( itkImporter->GetOutput() );
duplicator->Update();
// Store mask
m_InternalImageMask2D = duplicator->GetOutput();
}
void ImageStatisticsCalculator::UnmaskedStatisticsProgressUpdate()
{
// Need to throw away every second progress event to reach a final count of
// 100 since two consecutive filters are used in this case
static int updateCounter = 0;
if ( updateCounter++ % 2 == 0 )
{
this->InvokeEvent( itk::ProgressEvent() );
}
}
void ImageStatisticsCalculator::MaskedStatisticsProgressUpdate()
{
this->InvokeEvent( itk::ProgressEvent() );
}
-
}
diff --git a/Modules/ImageStatistics/mitkImageStatisticsCalculator.h b/Modules/ImageStatistics/mitkImageStatisticsCalculator.h
index 8af9c43d6c..d39faba4a8 100644
--- a/Modules/ImageStatistics/mitkImageStatisticsCalculator.h
+++ b/Modules/ImageStatistics/mitkImageStatisticsCalculator.h
@@ -1,346 +1,573 @@
/*===================================================================
-
The Medical Imaging Interaction Toolkit (MITK)
Copyright (c) German Cancer Research Center,
Division of Medical and Biological Informatics.
All rights reserved.
This software is distributed WITHOUT ANY WARRANTY; without
even the implied warranty of MERCHANTABILITY or FITNESS FOR
A PARTICULAR PURPOSE.
See LICENSE.txt or http://www.mitk.org for details.
===================================================================*/
-
#ifndef _MITK_IMAGESTATISTICSCALCULATOR_H
#define _MITK_IMAGESTATISTICSCALCULATOR_H
#include
#include "MitkImageStatisticsExports.h"
#include
#include
+#include "mitkImage.h"
+#include "mitkPlanarFigure.h"
#ifndef __itkHistogram_h
#include
#endif
+#include
-#include "mitkImage.h"
-#include "mitkImageTimeSelector.h"
-#include "mitkPlanarFigure.h"
#include
+// just a helper to unclutter our code
+// to be replaced with references to m_Member (when deprecated public members in Statistics are removed)
+#define mitkSetGetConstMacro(name, type) \
+ virtual type Get##name() const \
+ { \
+ return this->name; \
+ } \
+ \
+ virtual void Set##name(const type _arg) \
+ { \
+ if ( this->name != _arg ) \
+ { \
+ this->name = _arg; \
+ } \
+ }
+
namespace mitk
{
-
/**
* \brief Class for calculating statistics and histogram for an (optionally
* masked) image.
*
* Images can be masked by either a label image (of the same dimensions as
* the original image) or by a closed mitk::PlanarFigure, e.g. a circle or
* polygon. When masking with a planar figure, the slice corresponding to the
* plane containing the figure is extracted and then clipped with contour
* defined by the figure. Planar figures need to be aligned along the main axes
* of the image (axial, sagittal, coronal). Planar figures on arbitrary
* rotated planes are not supported.
*
* For each operating mode (no masking, masking by image, masking by planar
* figure), the calculated statistics and histogram are cached so that, when
* switching back and forth between operation modes without modifying mask or
* image, the information doesn't need to be recalculated.
*
+ * The class also has the possibility to calculate the location and separate
+ * statistics for a region called "hotspot". The hotspot is a sphere of
+ * user-defined size and its location is chosen in a way that the average
+ * pixel value within the sphere is maximized.
+ *
+ * \warning Hotspot calculation does not work in case of 2D-images!
+ *
* Note: currently time-resolved and multi-channel pictures are not properly
* supported.
- */
+ *
+ * \section HotspotStatistics_caption Calculation of hotspot statistics
+ *
+ * Since calculation of hotspot location and statistics is not
+ * straight-forward, the following paragraphs will describe it in more detail.
+ *
+ * Note: Calculation of hotspot statistics is optional and set to off by default.
+ * Multilabel-masks are supported.
+ *
+ * \subsection HotspotStatistics_description Hotspot Definition
+ *
+ * The hotspot of an image is motivated from PET readings. It is defined
+ * as a spherical region of fixed size which maximizes the average pixel value
+ * within the region. The following image illustrates the concept: the
+ * colored areas are different image intensities and the hotspot is located
+ * in the hottest region of the image.
+ *
+ * Note: Only hotspots are calculated for which the whole hotspot-sphere is
+ * inside the image by default. This behaviour can be changed by
+ * by calling SetHotspotMustBeCompletlyInsideImage().
+ * \warning Note that SetHotspotMustBeCompletlyInsideImage(false) may overrate
+ * "hot" regions at image borders, because they have a stronger influence on the
+ * mean value! Think clearly about this fact and make sure this is what you
+ * want/need in your application, before calling
+ * SetHotspotMustBeCompletlyInsideImage(false)!
+ *
+ *
+ * \image html hotspotexample.JPG
+ *
+ * \subsection HotspotStatistics_calculation Hotspot Calculation
+ *
+ * Since only the size of the hotspot is known initially, we need to calculate
+ * two aspects (both implemented in CalculateHotspotStatistics() ):
+ * - the hotspot location
+ * - statistics of the pixels within the hotspot.
+ *
+ * Finding the hotspot location requires to calculate the average value at each
+ * position. This is done by convolution of the image with a sperical kernel
+ * image which reflects partial volumes (important in the case of low-resolution
+ * PET images).
+ *
+ * Once the hotspot location is known, calculating the actual statistics is a
+ * simple task which is implemented in CalculateHotspotStatistics() using a second
+ * instance of the ImageStatisticsCalculator.
+ *
+ * Step 1: Finding the hotspot by image convolution
+ *
+ * As described above, we use image convolution with a rasterized sphere to
+ * average the image at each position. To handle coarse resolutions, which would
+ * normally force us to decide for partially contained voxels whether to count
+ * them or not, we supersample the kernel image and use non-integer kernel values
+ * (see GenerateHotspotSearchConvolutionKernel()), which reflect the volume part that is contained in the
+ * sphere. For example, if three subvoxels are inside the sphere, the corresponding
+ * kernel voxel gets a value of 0.75 (3 out of 4 subvoxels, see 2D example below).
+ *
+ * \image html convolutionkernelsupersampling.jpg
+ *
+ * Convolution itself is done by means of the itkFFTConvolutionImageFilter.
+ * To find the hotspot location, we simply iterate the averaged image and find a
+ * maximum location (see CalculateExtremaWorld()). In case of images with multiple
+ * maxima the method returns value and corresponding index of the extrema that is
+ * found by the iterator first.
+ *
+ * Step 2: Computation of hotspot statistics
+ *
+ * Once the hotspot location is found, statistics for the region are calculated
+ * by simply iterating the input image and regarding all pixel centers inside the
+ * hotspot-sphere for statistics.
+ * \warning Index positions of maximum/minimum are not provided, because they are not necessarily unique
+ * \todo If index positions of maximum/minimum are required, output needs to be changed to multiple positions / regions, etc.
+ *
+ * \subsection HotspotStatistics_tests Tests
+ *
+ * To check the correctness of the hotspot calculation, a special class
+ * (\ref hotspottestdoc) has been created, which generates images with
+ * known hotspot location and statistics. A number of unit tests use this class
+ * to first generate an image of known properites and then verify that
+ * ImageStatisticsCalculator is able to reproduce the known statistics.
+ *
+*/
class MitkImageStatistics_EXPORT ImageStatisticsCalculator : public itk::Object
{
public:
+ /** \brief Enum for possible masking modi. */
enum
{
MASKING_MODE_NONE = 0,
- MASKING_MODE_IMAGE,
- MASKING_MODE_PLANARFIGURE
+ MASKING_MODE_IMAGE = 1,
+ MASKING_MODE_PLANARFIGURE = 2
};
typedef itk::Statistics::Histogram HistogramType;
typedef HistogramType::ConstIterator HistogramConstIteratorType;
- struct Statistics
+ /** \brief Class for common statistics, includig hotspot properties. */
+ class MitkImageStatistics_EXPORT Statistics
{
- Statistics()
- {
- Reset();
- }
-
- int Label;
- unsigned int N;
- double Min;
- double Max;
- double Mean;
- double Median;
- double Variance;
- double Sigma;
- double RMS;
- vnl_vector< int > MinIndex;
- vnl_vector< int > MaxIndex;
-
- void Reset()
- {
- Label = 0;
- N = 0;
- Min = 0.0;
- Max = 0.0;
- Mean = 0.0;
- Median = 0.0;
- Variance = 0.0;
- Sigma = 0.0;
- RMS = 0.0;
- }
+ public:
+
+ Statistics(bool withHotspotStatistics = true);
+ Statistics(const Statistics& other);
+
+ virtual ~Statistics();
+
+ Statistics& operator=(Statistics const& stats);
+
+ const Statistics& GetHotspotStatistics() const; // real statistics
+ Statistics& GetHotspotStatistics(); // real statistics
+ bool HasHotspotStatistics() const;
+ void SetHasHotspotStatistics(bool hasHotspotStatistics); // set a flag. if set, return empty hotspotstatistics object
+
+ void Reset(unsigned int dimension = 2);
+
+ mitkSetGetConstMacro(Label, unsigned int)
+ mitkSetGetConstMacro(N, unsigned int)
+ mitkSetGetConstMacro(Min, double)
+ mitkSetGetConstMacro(Max, double)
+ mitkSetGetConstMacro(Mean, double)
+ mitkSetGetConstMacro(Median, double)
+
+ double GetVariance() const;
+ /** \brief Set variance
+ *
+ * This method checks whether the variance is negative:
+ * The reason that the variance may be negative is that the underlying itk::LabelStatisticsImageFilter uses a naïve algorithm
+ * for calculating the variance ( http://en.wikipedia.org/wiki/Algorithms_for_calculating_variance ) which can lead to negative values
+ * due to rounding errors.
+ *
+ * If the variance is negative the value will be set to 0.0, else the given value will be set.
+ */
+ void SetVariance( const double );
+
+ double GetSigma() const;
+ /** \brief Set standard deviation (sigma)
+ *
+ * This method checks if the given standard deviation is a positive value. This is done because the underlying itk::LabelStatisticsImageFilter uses
+ * a naïve algorithm to calculate the variance. This may lead to a negative variance and because the square root of the variance is taken it also
+ * leads to NaN for sigma.
+ *
+ * If the given value is not reasonable the value will be set to 0.0, else the given value will be set.
+ *
+ * \see SetVariance()
+ */
+ void SetSigma( const double );
+
+ mitkSetGetConstMacro(RMS, double)
+ mitkSetGetConstMacro(MinIndex, vnl_vector)
+ mitkSetGetConstMacro(MaxIndex, vnl_vector)
+ mitkSetGetConstMacro(HotspotIndex, vnl_vector)
+
+ private:
+ unsigned int Label;
+ unsigned int N;
+ double Min;
+ double Max;
+ double Mean;
+ double Median;
+ double Variance;
+ double Sigma;
+ double RMS;
+ vnl_vector MinIndex;
+ vnl_vector MaxIndex;
+
+ Statistics* m_HotspotStatistics;
+
+ bool m_HasHotspotStatistics;
+ vnl_vector HotspotIndex; //< index of hotspotsphere origin
};
typedef std::vector< HistogramType::ConstPointer > HistogramContainer;
typedef std::vector< Statistics > StatisticsContainer;
-
mitkClassMacro( ImageStatisticsCalculator, itk::Object );
itkFactorylessNewMacro(Self)
itkCloneMacro(Self)
/** \brief Automatically calculate bin size to obtain 200 bins. */
void SetUseDefaultBinSize(bool useDefault);
/** \brief Set image from which to compute statistics. */
void SetImage( const mitk::Image *image );
/** \brief Set image for masking. */
void SetImageMask( const mitk::Image *imageMask );
/** \brief Set planar figure for masking. */
void SetPlanarFigure( mitk::PlanarFigure *planarFigure );
/** \brief Set/Get operation mode for masking */
void SetMaskingMode( unsigned int mode );
/** \brief Set/Get operation mode for masking */
itkGetMacro( MaskingMode, unsigned int );
/** \brief Set/Get operation mode for masking */
void SetMaskingModeToNone();
/** \brief Set/Get operation mode for masking */
void SetMaskingModeToImage();
/** \brief Set/Get operation mode for masking */
void SetMaskingModeToPlanarFigure();
/** \brief Set a pixel value for pixels that will be ignored in the statistics */
void SetIgnorePixelValue(double value);
/** \brief Get the pixel value for pixels that will be ignored in the statistics */
double GetIgnorePixelValue();
- /** \brief Set wether a pixel value should be ignored in the statistics */
+ /** \brief Set whether a pixel value should be ignored in the statistics */
void SetDoIgnorePixelValue(bool doit);
- /** \brief Get wether a pixel value will be ignored in the statistics */
+ /** \brief Get whether a pixel value will be ignored in the statistics */
bool GetDoIgnorePixelValue();
/** \brief Set bin size for histogram resolution.*/
void SetHistogramBinSize( unsigned int size);
/** \brief Get bin size for histogram resolution.*/
unsigned int GetHistogramBinSize();
+ /** \brief Sets the radius for the hotspot */
+ void SetHotspotRadiusInMM (double hotspotRadiusInMM);
+
+ /** \brief Returns the radius of the hotspot */
+ double GetHotspotRadiusInMM();
+
+ /** \brief Sets whether the hotspot should be calculated */
+ void SetCalculateHotspot(bool calculateHotspot);
+
+ /** \brief Returns true whether the hotspot should be calculated, otherwise false */
+ bool IsHotspotCalculated();
+
+ /** \brief Sets flag whether hotspot is completly inside the image. Please note that if set to false
+ it can be possible that statistics are calculated for which the whole hotspot is not inside the image!
+
+ \warning regarding positions at the image centers may produce unexpected hotspot locations, please see \ref HotspotStatistics_description
+ */
+ void SetHotspotMustBeCompletlyInsideImage(bool hotspotIsCompletlyInsideImage, bool warn = true);
+
+ /** \brief Returns true if hotspot has to be completly inside the image. */
+ bool GetHotspotMustBeCompletlyInsideImage() const;
+
/** \brief Compute statistics (together with histogram) for the current
* masking mode.
*
* Computation is not executed if statistics is already up to date. In this
* case, false is returned; otherwise, true.*/
virtual bool ComputeStatistics( unsigned int timeStep = 0 );
/** \brief Retrieve the histogram depending on the current masking mode.
*
* \param label The label for which to retrieve the histogram in multi-label situations (ascending order).
*/
const HistogramType *GetHistogram( unsigned int timeStep = 0, unsigned int label = 0 ) const;
/** \brief Retrieve the histogram depending on the current masking mode (for all image labels. */
const HistogramContainer &GetHistogramVector( unsigned int timeStep = 0 ) const;
/** \brief Retrieve statistics depending on the current masking mode.
*
* \param label The label for which to retrieve the statistics in multi-label situations (ascending order).
*/
const Statistics &GetStatistics( unsigned int timeStep = 0, unsigned int label = 0 ) const;
/** \brief Retrieve statistics depending on the current masking mode (for all image labels). */
const StatisticsContainer &GetStatisticsVector( unsigned int timeStep = 0 ) const;
protected:
typedef std::vector< HistogramContainer > HistogramVector;
typedef std::vector< StatisticsContainer > StatisticsVector;
typedef std::vector< itk::TimeStamp > TimeStampVectorType;
typedef std::vector< bool > BoolVectorType;
-
-
typedef itk::Image< unsigned short, 3 > MaskImage3DType;
typedef itk::Image< unsigned short, 2 > MaskImage2DType;
ImageStatisticsCalculator();
virtual ~ImageStatisticsCalculator();
/** \brief Depending on the masking mode, the image and mask from which to
* calculate statistics is extracted from the original input image and mask
* data.
*
* For example, a when using a PlanarFigure as mask, the 2D image slice
* corresponding to the PlanarFigure will be extracted from the original
* image. If masking is disabled, the original image is simply passed
* through. */
void ExtractImageAndMask( unsigned int timeStep = 0 );
/** \brief If the passed vector matches any of the three principal axes
* of the passed geometry, the ínteger value corresponding to the axis
* is set and true is returned. */
bool GetPrincipalAxis( const BaseGeometry *geometry, Vector3D vector,
unsigned int &axis );
template < typename TPixel, unsigned int VImageDimension >
void InternalCalculateStatisticsUnmasked(
const itk::Image< TPixel, VImageDimension > *image,
StatisticsContainer* statisticsContainer,
HistogramContainer *histogramContainer );
template < typename TPixel, unsigned int VImageDimension >
void InternalCalculateStatisticsMasked(
const itk::Image< TPixel, VImageDimension > *image,
itk::Image< unsigned short, VImageDimension > *maskImage,
StatisticsContainer* statisticsContainer,
HistogramContainer* histogramContainer );
template < typename TPixel, unsigned int VImageDimension >
void InternalCalculateMaskFromPlanarFigure(
const itk::Image< TPixel, VImageDimension > *image, unsigned int axis );
template < typename TPixel, unsigned int VImageDimension >
void InternalMaskIgnoredPixels(
const itk::Image< TPixel, VImageDimension > *image,
itk::Image< unsigned short, VImageDimension > *maskImage );
+ class ImageExtrema
+ {
+ public:
+ bool Defined;
+ double Max;
+ double Min;
+ vnl_vector MaxIndex;
+ vnl_vector MinIndex;
+
+ ImageExtrema()
+ :Defined(false)
+ ,Max(itk::NumericTraits::min())
+ ,Min(itk::NumericTraits::max())
+ {
+ }
+ };
+
+
+ /** \brief Calculates minimum, maximum, mean value and their
+ * corresponding indices in a given ROI. As input the function
+ * needs an image and a mask. Returns an ImageExtrema object. */
+ template
+ ImageExtrema CalculateExtremaWorld(
+ const itk::Image *inputImage,
+ itk::Image *maskImage,
+ double neccessaryDistanceToImageBorderInMM,
+ unsigned int label);
+
+
+ /** \brief Calculates the hotspot statistics depending on
+ * masking mode. Hotspot statistics are calculated for a
+ * hotspot which is completly located inside the image by default. */
+ template < typename TPixel, unsigned int VImageDimension>
+ Statistics CalculateHotspotStatistics(
+ const itk::Image *inputImage,
+ itk::Image *maskImage,
+ double radiusInMM,
+ bool& isHotspotDefined,
+ unsigned int label);
+
/** Connection from ITK to VTK */
template
void ConnectPipelines(ITK_Exporter exporter, vtkSmartPointer importer)
{
importer->SetUpdateInformationCallback(exporter->GetUpdateInformationCallback());
importer->SetPipelineModifiedCallback(exporter->GetPipelineModifiedCallback());
importer->SetWholeExtentCallback(exporter->GetWholeExtentCallback());
importer->SetSpacingCallback(exporter->GetSpacingCallback());
importer->SetOriginCallback(exporter->GetOriginCallback());
importer->SetScalarTypeCallback(exporter->GetScalarTypeCallback());
importer->SetNumberOfComponentsCallback(exporter->GetNumberOfComponentsCallback());
importer->SetPropagateUpdateExtentCallback(exporter->GetPropagateUpdateExtentCallback());
importer->SetUpdateDataCallback(exporter->GetUpdateDataCallback());
importer->SetDataExtentCallback(exporter->GetDataExtentCallback());
importer->SetBufferPointerCallback(exporter->GetBufferPointerCallback());
importer->SetCallbackUserData(exporter->GetCallbackUserData());
}
/** Connection from VTK to ITK */
template
void ConnectPipelines(vtkSmartPointer exporter, ITK_Importer importer)
{
importer->SetUpdateInformationCallback(exporter->GetUpdateInformationCallback());
importer->SetPipelineModifiedCallback(exporter->GetPipelineModifiedCallback());
importer->SetWholeExtentCallback(exporter->GetWholeExtentCallback());
importer->SetSpacingCallback(exporter->GetSpacingCallback());
importer->SetOriginCallback(exporter->GetOriginCallback());
importer->SetScalarTypeCallback(exporter->GetScalarTypeCallback());
importer->SetNumberOfComponentsCallback(exporter->GetNumberOfComponentsCallback());
importer->SetPropagateUpdateExtentCallback(exporter->GetPropagateUpdateExtentCallback());
importer->SetUpdateDataCallback(exporter->GetUpdateDataCallback());
importer->SetDataExtentCallback(exporter->GetDataExtentCallback());
importer->SetBufferPointerCallback(exporter->GetBufferPointerCallback());
importer->SetCallbackUserData(exporter->GetCallbackUserData());
}
void UnmaskedStatisticsProgressUpdate();
void MaskedStatisticsProgressUpdate();
+ /** \brief Returns size of convolution kernel depending on spacing and radius. */
+ template
+ itk::Size
+ CalculateConvolutionKernelSize(double spacing[VImageDimension], double radiusInMM);
+
+ /** \brief Generates image of kernel which is needed for convolution. */
+ template
+ itk::SmartPointer< itk::Image >
+ GenerateHotspotSearchConvolutionKernel(double spacing[VImageDimension], double radiusInMM);
+
+ /** \brief Convolves image with spherical kernel image. Used for hotspot calculation. */
+ template
+ itk::SmartPointer< itk::Image >
+ GenerateConvolutionImage( const itk::Image* inputImage );
+
+ /** \brief Fills pixels of the spherical hotspot mask. */
+ template < typename TPixel, unsigned int VImageDimension>
+ void
+ FillHotspotMaskPixels( itk::Image* maskImage,
+ itk::Point sphereCenter,
+ double sphereRadiusInMM);
/** m_Image contains the input image (e.g. 2D, 3D, 3D+t)*/
mitk::Image::ConstPointer m_Image;
mitk::Image::ConstPointer m_ImageMask;
mitk::PlanarFigure::Pointer m_PlanarFigure;
HistogramVector m_ImageHistogramVector;
HistogramVector m_MaskedImageHistogramVector;
HistogramVector m_PlanarFigureHistogramVector;
HistogramType::Pointer m_EmptyHistogram;
HistogramContainer m_EmptyHistogramContainer;
StatisticsVector m_ImageStatisticsVector;
StatisticsVector m_MaskedImageStatisticsVector;
StatisticsVector m_PlanarFigureStatisticsVector;
+ StatisticsVector m_MaskedImageHotspotStatisticsVector;
Statistics m_EmptyStatistics;
StatisticsContainer m_EmptyStatisticsContainer;
unsigned int m_MaskingMode;
bool m_MaskingModeChanged;
/** m_InternalImage contains a image volume at one time step (e.g. 2D, 3D)*/
mitk::Image::ConstPointer m_InternalImage;
MaskImage3DType::Pointer m_InternalImageMask3D;
MaskImage2DType::Pointer m_InternalImageMask2D;
TimeStampVectorType m_ImageStatisticsTimeStampVector;
TimeStampVectorType m_MaskedImageStatisticsTimeStampVector;
TimeStampVectorType m_PlanarFigureStatisticsTimeStampVector;
BoolVectorType m_ImageStatisticsCalculationTriggerVector;
BoolVectorType m_MaskedImageStatisticsCalculationTriggerVector;
BoolVectorType m_PlanarFigureStatisticsCalculationTriggerVector;
double m_IgnorePixelValue;
bool m_DoIgnorePixelValue;
bool m_IgnorePixelValueChanged;
unsigned int m_PlanarFigureAxis; // Normal axis for PlanarFigure
unsigned int m_PlanarFigureSlice; // Slice which contains PlanarFigure
int m_PlanarFigureCoordinate0; // First plane-axis for PlanarFigure
int m_PlanarFigureCoordinate1; // Second plane-axis for PlanarFigure
unsigned int m_HistogramBinSize; ///Bin size for histogram resoluion.
bool m_UseDefaultBinSize;
+ double m_HotspotRadiusInMM;
+ bool m_CalculateHotspot;
+ bool m_HotspotRadiusInMMChanged;
+ bool m_HotspotMustBeCompletelyInsideImage;
};
-}
+} // namespace
-#endif // #define _MITK_IMAGESTATISTICSCALCULATOR_H
+#endif
diff --git a/Modules/ImageStatistics/mitkImageStatisticsHotspotTest.dox b/Modules/ImageStatistics/mitkImageStatisticsHotspotTest.dox
new file mode 100644
index 0000000000..a2095fedb2
--- /dev/null
+++ b/Modules/ImageStatistics/mitkImageStatisticsHotspotTest.dox
@@ -0,0 +1,107 @@
+/**
+ \defgroup hotspottestdoc mitkImageStatisticsHotspotTest
+ \section hotspotCalculationTestCases Testcases
+
+ To check the correctness of the hotspot calculation, this special class has been created, which
+ generates images with known hotspot location and statistics. A number of unit tests use this class to first generate
+ an image of known properties and then verify that \ref mitk::ImageStatisticsCalculator is able to reproduce the known statistics.
+
+ Every testcase has a defined hotspot, maximum and minimum including their corresponding index-values and mean value.
+ The XML-files to each testcase is located in Modules/ImageStatistics/Testing/Data.
+
+ This test checks the hotspot-statistics of images with a spacing[x,y,z] of [3,3,3], [4,4,3] and [5,5,5], according to common PET-resolutions.
+
+ The following cases describe situations of hotspot-calculation and their supposed results.
+
+ Note: Below only the behaviour of maximum is mentioned mostly, but the other statistics (minimum and mean) behave
+ in the same way like maximum.
+
+ Testcase 1: No values outside of hotspot are used for statistic-calculation
+
+ The purpose of this testcase is primarily to confirm the correct detection of the hotspot even if there is an global maximum
+ which is "hotter" than the mean value itself. On the other hand the test verifies that only voxels are used for statistic-calculation
+ which are located in the hotspot.
+
+ Description:
+ - Defined location of hotspot in image: left upper corner
+ - Defined location of maximum in image: bottom right corner
+ - Segmentation is not available
+
+ \image html mitkimagestatisticshotspottestcase1.jpg
+
+ Assumed results:
+ - Hotspot is calculated correctly in the left upper corner of the image
+ - Defined maximum is not inside hotspot
+ - A maximum inside the hotspot is calculated
+
+ Testcase 2: Correct detection of hotspot
+
+ In this testcase we want to make sure that when a segmentation is available the origin of the hotspot-sphere is located within it. The
+ image is so structured that there are two hot regions: One region inside and another one, which is hotter than the other region, outside the segmentation.
+ So we can assume that the segmentation is also considered when detecting the hotspot, even an actual hotspot outside the segmentation exists.
+
+ Description:
+ - Segmentation is available
+ - Defined location of hotspot: inside segmentation
+ - Defined location of maximum: inside hotspot
+ - Another "hotter" region outside of the segmentation
+
+ \image html mitkimagestatisticshotspottestcase2.jpg
+
+ Assumed results:
+ - Defined hotspot is correctly calculated inside segmentation
+ - Defined maximum is correctly calculated inside hotspot
+ - "Hotter" region outside of segmentation is disregarded
+
+ Testcase 3: Correct calculation of statistics in hotspot, although the whole hotspot is not inside segmentation
+
+ The difficulty of calculating the hotspot statistics in testcase 3 is that the origin of the hotspot is close to the segmentation-borders. So
+ if the whole hotspot is not inside the segmentation (or even the segmentation is smaller than the hotspot itself) this test checks that
+ calculation of hotspot statistics is possible anyway.
+
+ Description:
+ - Segmentation is available
+ - Defined location of hotspot: inside segmentation
+ - Defined location of maximum: outside of segmentation, but inside of hotspot
+
+ \image html mitkimagestatisticshotspottestcase3.jpg
+
+ Assumed results:
+ - Defined hotspot is correctly calculated inside segmentation
+ - Defined maximum is correctly calculated inside hotspot although it is located outside of the segmentation
+
+ Testcase 4 and 5: Hotspot must (not) be completely inside image
+
+ Testcase 4 and 5 are very similar so we mention it at the same time: In testcase 4 the hotspot is not completely inside the image and just
+ voxels are considered for calculation which are located inside the image. But in testcase 5 the hotspot must be completely inside the image
+ even there is an possible hotspot-location at the borders of the image.
+
+ Description:
+ - Defined location of hotspot: At the border of the image
+ - Defined location of maximum: Inside hotspot
+ - Segmentation is not available
+
+ \image html mitkimagestatisticshotspottestcase5.jpg
+
+ Assumed results in testcase 4:
+ - Just the part of the hotspot, which is located in the image, is used for statistics-calculation
+ - Defined statistics are calculated correctly
+
+ Assumed results in testcase 5:
+ - Defined hotspot and statistics are not calculated, because hotspot is not completely inside image
+ - A hotspot, which is not as hot as the defined one but is inside the image, is calculated
+
+
+ Testcase 6: Multi label mask
+
+ This testcase confirms that mitkImageStatisticsCalculator has the possibility to calculate hotspot statistics even if
+ there are multiple regions of interest.
+
+ Description:
+ - Two defined regions of interest with defined statistics for each one.
+
+ \image html mitkimagestatisticshotspottestcase6.jpg
+
+ Assumed results:
+ - In every region of interest there are correctly calculated hotspot-statistics
+ */
\ No newline at end of file
diff --git a/Modules/ImageStatistics/mitkPointSetDifferenceStatisticsCalculator.cpp b/Modules/ImageStatistics/mitkPointSetDifferenceStatisticsCalculator.cpp
index 8d2173d8df..8e5d173598 100644
--- a/Modules/ImageStatistics/mitkPointSetDifferenceStatisticsCalculator.cpp
+++ b/Modules/ImageStatistics/mitkPointSetDifferenceStatisticsCalculator.cpp
@@ -1,214 +1,214 @@
/*===================================================================
The Medical Imaging Interaction Toolkit (MITK)
Copyright (c) German Cancer Research Center,
Division of Medical and Biological Informatics.
All rights reserved.
This software is distributed WITHOUT ANY WARRANTY; without
even the implied warranty of MERCHANTABILITY or FITNESS FOR
A PARTICULAR PURPOSE.
See LICENSE.txt or http://www.mitk.org for details.
===================================================================*/
#include "mitkPointSetDifferenceStatisticsCalculator.h"
mitk::PointSetDifferenceStatisticsCalculator::PointSetDifferenceStatisticsCalculator() :
m_StatisticsCalculated(false)
{
m_PointSet1 = mitk::PointSet::New();
m_PointSet2 = mitk::PointSet::New();
- m_Statistics.Reset();
+ //m_Statistics.Reset();
}
mitk::PointSetDifferenceStatisticsCalculator::PointSetDifferenceStatisticsCalculator(mitk::PointSet::Pointer pSet1, mitk::PointSet::Pointer pSet2)
{
m_PointSet1 = pSet1;
m_PointSet2 = pSet2;
m_StatisticsCalculated = false;
- m_Statistics.Reset();
+ //m_Statistics.Reset();
}
mitk::PointSetDifferenceStatisticsCalculator::~PointSetDifferenceStatisticsCalculator()
{
}
void mitk::PointSetDifferenceStatisticsCalculator::SetPointSets(mitk::PointSet::Pointer pSet1, mitk::PointSet::Pointer pSet2)
{
if (pSet1.IsNotNull())
{
m_PointSet1 = pSet1;
}
if (pSet2.IsNotNull())
{
m_PointSet2 = pSet2;
}
m_StatisticsCalculated = false;
- m_Statistics.Reset();
+ //m_Statistics.Reset();
}
std::vector mitk::PointSetDifferenceStatisticsCalculator::GetDifferences()
{
if (!m_StatisticsCalculated)
{
this->ComputeStatistics();
}
return m_DifferencesVector;
}
std::vector mitk::PointSetDifferenceStatisticsCalculator::GetSquaredDifferences()
{
if (!m_StatisticsCalculated)
{
this->ComputeStatistics();
}
return m_SquaredDifferencesVector;
}
double mitk::PointSetDifferenceStatisticsCalculator::GetMean()
{
if (!m_StatisticsCalculated)
{
this->ComputeStatistics();
}
- return m_Statistics.Mean;
+ return m_Statistics.GetMean();
}
double mitk::PointSetDifferenceStatisticsCalculator::GetSD()
{
if (!m_StatisticsCalculated)
{
this->ComputeStatistics();
}
- return m_Statistics.Sigma;
+ return m_Statistics.GetSigma();
}
double mitk::PointSetDifferenceStatisticsCalculator::GetVariance()
{
if (!m_StatisticsCalculated)
{
this->ComputeStatistics();
}
- return m_Statistics.Variance;
+ return m_Statistics.GetVariance();
}
double mitk::PointSetDifferenceStatisticsCalculator::GetRMS()
{
if (!m_StatisticsCalculated)
{
this->ComputeStatistics();
}
- return m_Statistics.RMS;
+ return m_Statistics.GetRMS();
}
double mitk::PointSetDifferenceStatisticsCalculator::GetMedian()
{
if (!m_StatisticsCalculated)
{
this->ComputeStatistics();
}
- return m_Statistics.Median;
+ return m_Statistics.GetMedian();
}
double mitk::PointSetDifferenceStatisticsCalculator::GetMax()
{
if (!m_StatisticsCalculated)
{
this->ComputeStatistics();
}
- return m_Statistics.Max;
+ return m_Statistics.GetMax();
}
double mitk::PointSetDifferenceStatisticsCalculator::GetMin()
{
if (!m_StatisticsCalculated)
{
this->ComputeStatistics();
}
- return m_Statistics.Min;
+ return m_Statistics.GetMin();
}
double mitk::PointSetDifferenceStatisticsCalculator::GetNumberOfPoints()
{
if (!m_StatisticsCalculated)
{
this->ComputeStatistics();
}
- return m_Statistics.N;
+ return m_Statistics.GetN();
}
void mitk::PointSetDifferenceStatisticsCalculator::ComputeStatistics()
{
if ((m_PointSet1.IsNull())||(m_PointSet2.IsNull()))
{
itkExceptionMacro("Point sets specified are not valid. Please specify correct Point sets");
}
else if (m_PointSet1->GetSize()!=m_PointSet2->GetSize())
{
itkExceptionMacro("PointSets are not equal. Please make sure that your PointSets have the same size and hold corresponding points.");
}
else if (m_PointSet1->GetSize()==0)
{
itkExceptionMacro("There are no points in the PointSets. Please make sure that the PointSets contain points");
}
else
{
double mean = 0.0;
double sd = 0.0;
double rms= 0.0;
std::vector differencesVector;
mitk::Point3D point1;
mitk::Point3D point2;
int numberOfPoints = m_PointSet1->GetSize();
//Iterate over both pointsets in order to compare all points pair-wise
mitk::PointSet::PointsIterator end = m_PointSet1->End();
for( mitk::PointSet::PointsIterator pointSetIterator = m_PointSet1->Begin(), pointSetIterator2 = m_PointSet2->Begin();
pointSetIterator != end; ++pointSetIterator, ++pointSetIterator2) //iterate simultaneously over both sets
{
point1 = pointSetIterator.Value();
point2 = pointSetIterator2.Value();
double squaredDistance = point1.SquaredEuclideanDistanceTo(point2);
mean+=sqrt(squaredDistance);
rms+=squaredDistance;
this->m_SquaredDifferencesVector.push_back(squaredDistance);
differencesVector.push_back(sqrt(squaredDistance));
}
m_DifferencesVector = differencesVector;
mean = mean/numberOfPoints;
rms = sqrt(rms/numberOfPoints);
for (std::vector::size_type i=0; i
#include
// berry includes
#include
// mitk includes
#include "mitkNodePredicateDataType.h"
#include "mitkPlanarFigureInteractor.h"
// itk includes
#include "itksys/SystemTools.hxx"
#include
#include