diff --git a/Plugins/org.mitk.gui.qt.datamanager/documentation/UserManual/QmitkDatamanager.dox b/Plugins/org.mitk.gui.qt.datamanager/documentation/UserManual/QmitkDatamanager.dox index 08e636a260..2fa38bbc7c 100644 --- a/Plugins/org.mitk.gui.qt.datamanager/documentation/UserManual/QmitkDatamanager.dox +++ b/Plugins/org.mitk.gui.qt.datamanager/documentation/UserManual/QmitkDatamanager.dox @@ -1,109 +1,109 @@ /** \page org_mitk_views_datamanager The DataManager \imageMacro{data-manager.svg,"Icon of the Data Manager",2.00} \tableofcontents \section QmitkDataManagerIntroduction Introduction The Datamanager is the central componenent to manage medical data like images, surfaces, etc.. After loading one or more data into the Datamanager the data are shown in the four-view window, the so called Standard View. The user can now start working on the data by just clicking into the standard view or by using the MITK-modules such as "Segmentation" or "Basic Image Processing". \imageMacro{QmitkDatamanager_Overview.png,"How MITK looks when started",16.00} \section QmitkDataManagerLoading Loading Data There are three ways of loading data into the Datamanager as so called Data-Elements. The user can just drag and drop data into the Datamanager or directly into one of the four parts of the Standard View. He can as well use the Open-Button in the right upper corner. Or he can use the standard "File->Open"-Dialog on the top. A lot of file-formats can be loaded into MITK, for example The user can also load a series of 2D images (e.g. image001.png, image002.png ...) to a MITK 3D volume. To do this, just drag and drop one of those 2D data files into the Datamanager by holding the ALT key. After loading one or more data into the Datamanager they appear as Data-Elements in a sorted list inside the Datamanager. Data-Elements can also be sorted hierarchically as a parent-child-relation. For example after using the Segmentation-Module on Data-Element1 the result is created as Data-Element2, which is a child of Data-Element1 (see Screenshot1). The order can be changed by drag and drop. \imageMacro{QmitkDatamanager_ParentChild.png,"Screenshot1",9.61} The listed Data-Elements are shown in the standard view. Here the user can scale or rotate the medical objects or he can change the cutting planes of the object by just using the mouse inside this view. \section QmitkDataManagerSaving Saving Data -There are two ways of saving data from the Datamanger. The user can either save the whole project with all Data-Elements by clicking on "File"->"Save Project" +There are two ways of saving data from the Datamanager. The user can either save the whole project with all Data-Elements by clicking on "File"->"Save Project" or he can save single Data-Elements by right-clicking->"Save", directly on a Data-Element. When saving the whole project, the sorting of Data-Elements is saved as well. By contrast the sorting is lost, when saving a single Data-Element. \section QmitkDataManagerProperties Working with the Datamanager \subsection QmitkDataManagerPropertiesList List of Data-Elements The Data-Elements are listed in the Datamanager. As described above the elements can be sorted hierarchically as a parent-child-relation. For example after using the Segmentation-Module on Data-Element1 the result is created as Data-Element2, which is a child of Data-Element1 (see Screenshot1). By drag and drop the sorting of Data-Elements and their hierarchical relation can be changed. \subsection QmitkDataManagerPropertiesVisibility Visibility of Data-Elements By default all loaded Data-Elements are visible in the standard view. The visibility can be changed by right-clicking on the Data-Element and then choosing "Toogle visibility". The box in front of the Data-Element in the Datamanager shows the visibility. A green-filled box means a visible Data-Element, an empty box means an invisible Data-Element (see Screenshot1). \subsection QmitkDataManagerPropertiesRepresentation Representation of Data-Elements There are different types of representations how to show the Data-Element inside the standard view. By right-clicking on the Data-Element all options are listed (see Screenshot2 and Screenshot 3). \imageMacro{QmitkDatamanager_ImageProperties.png,"Screenshot2: Properties for images",10.56} \imageMacro{QmitkDatamanager_SurfaceProperties.png,"Screenshot3: Properties for surfaces",11.01} \subsection QmitkDataManagerPropertiesPreferences Preferences For the datamanager there are already some default hotkeys like the del-key for deleting a Data-Element. The whole list is seen in Screenshot4. From here the Hotkeys can also be changed. The preference page is found in "Window"->"Preferences". \imageMacro{QmitkDatamanager_Preferences.png,"Screenshot4",16.00} \section QmitkDataManagerPropertyList Property List The Property List displays all the properties the currently selected Data-Element has. Which properties these are depends on the Data-Element. Examples are opacity, shader, visibility. These properties can be changed by clicking on the appropriate field in the "value" column. \imageMacro{QmitkDatamanager_PropertyList.png,"Screenshot5: Property List",7.85} */ diff --git a/Plugins/org.mitk.gui.qt.matchpoint.mapper/documentation/UserManual/Manual.dox b/Plugins/org.mitk.gui.qt.matchpoint.mapper/documentation/UserManual/Manual.dox index c02863a2a6..bc09666a68 100644 --- a/Plugins/org.mitk.gui.qt.matchpoint.mapper/documentation/UserManual/Manual.dox +++ b/Plugins/org.mitk.gui.qt.matchpoint.mapper/documentation/UserManual/Manual.dox @@ -1,85 +1,85 @@ /** \page org_mitk_gui_qt_matchpoint_mapper The MatchPoint Image Mapper View \imageMacro{map_mapper_icon_doc.svg, "Icon of the MatchPoint Image Mapper",3} \tableofcontents \section MAP_MAPPER_Introduction Introduction This view offers the possibility to map any image or point set in the data manager using a user selected registration object. Using the Mapper to map images the user can control the field of view (image geometry) the image should be mapped into, as well as interpolation strategy that should be used.\n It is one of several MatchPoint registration plugins.\n Typical usage scenarios\n \li You have registered image I1 onto image I2. Now you want to transfer the segmentation of I1 to I2 in order to evaluate I2 within this mapped segmentation using \ref org_mitk_views_imagestatistics . \li You have registered image I1 onto image I2. Now you want to map I3 (e.g. an other MRI sequence of the same session) also onto I2 with the same registration. \li You have registered image I1 onto image I2. Now you want to map a segmentation done on I1 also onto I2 with the same registration. \li You have registered image I1 onto image I2. Now you want to map a point set of image I1 also onto I2 with the same registration. \section MAP_MAPPER_Contact Contact information This plug-in is being developed by the SIDT group (Software development for Integrated Diagnostics and Therapy) at the DKFZ (German Cancer Research Center). If you have any questions, need support, find a bug or have a feature request, feel free to contact us at www.mitk.org. \section MAP_MAPPER_Usage Usage \imageMacro{map_mapper-examplescreen.png, "Example screenshot showing the Mapper plugin in use.", 14} To use the mapper at least an input data (image or point set) must be selected. Additionally you may select a registration object and a reference image. Registration objects are marked with a small blue icon (e.g. the data "Registration" in the data manager of the screen shot above). The Reference image defines the geometry (field of view, orientation, spacing) that should be used for the result image. By default the view will try to automatically determine the reference image (by default it is the target image of the selected registration). If auto selection cannot determine the reference it will choose the input image as reference. The reference image can be also defined by the user explicitly by activating manual selection.\n REMARK: If you map point sets you can ignore the reference image slot. It has no affect.\n You can multi select registration and data (press the CTRL-key while selecting the nodes in the data manager). The Mapper will automatically sort the selections in the correct "slots" of the view.\n REMARK: The mapping results will be added as child nodes to the used input node.\n REMARK: If you do not select an registration the view will assume that you make an identity transform. This is a convenient way if you just want to resample an image into the geometry of an other image (when no registration is needed). Also in this use case you can take advantage of the different interpolation and sub/super sampling strategies. \imageMacro{map_mapper.png, "Details of the mapper view.", 8} (1) The currently selected registration, that will be used for mapping.\n (2) The currently selected input data, that will be mapped.\n (3) The currently (automatically or by user) selected reference image, that defines the geometry of the result.\n -(4) The name of the result data in the data manger.\n +(4) The name of the result data in the data manager.\n (5) The start button(s) to commence the mapping process. For details regarding the two options see \ref MAP_MAPPER_Refine.\n (6) Log windows with messages regarding the mapping process.\n\n Every "slot" has the ability to be locked. If locked the last selection will be kept, regardless the current selection in the data manager. You can use this for example to lock the registration, if you want to map multiple images. Doing so it is enough to just select the next image in the data manager. To lock a slot, click at the "lock" button at the right side (see example images below). \imageMacro{map_node-unlocked.png, "Unlocked slot/node (default state). Changes with the selections in the data manager.",6} \imageMacro{map_node-locked.png, "Locked slot/node. Stays, regardless the selections in the data manager.",6} \section MAP_MAPPER_Refine Mapping or geometry refinement The mapper view offers two options to map images:\n \li "Map" (default) \li "Refine geometry" For images "Map" fills the pixels of the output image by interpolating input image pixels using the registration object. This option always works. But may take longer and introduces interpolation errors, because a new image is resampled.\n The second option "Refine geometry" is only offered, if the registration (more precise its inverse kernel) is matrix based and the selected data is an image. In this case it just clones the image and refines its image geometry (origin and orientation) to project it to the position indicated by the registration; thus no interpolation artefacts are introduced. \remark If you want to use a mapped image in conjunction with the statistic plugin and an mask of the reference image (or you want to proceed any other computation that expects the voxel to be in the same grid for direct numeric comparison), you must use "Map" to ensure the same geometry (including the same image grid; including same spacing and resolution). Otherwise operations like the statistic plugin will fail. \section MAP_MAPPER_Settings Settings If you map the image (and not just refine the geometry), you have several settings available:\n \li "Allow undefined pixels": Activate to handle pixels of the result image that are not in the field of view of the input image. This pixel will get the "padding value". \li "Allow error pixels": Activate to handle pixels of the result image that can not be mapped because the registration does not support this part of the output image. This pixel will get the "error value". \li "Interpolator": Set to choose the interpolation strategy that should be used for mapping. \li "Activate super/sub sampling": Activate if you want to use origin and orientation of the reference image but want to alter the spacing. \section MAP_MAPPER_Interpolation Interpolation You can choose from the following interpolation strategies:\n \li "nearest neighbor": Use the value of the nearest pixel. Fastest, but high interpolation errors for gray value images. Right choice for label images or masks. \li "Linear": Fast linear interpolation with often sufficient quality. Tends to blur edges. \li "BSpline (3rd order)": Good trade off between time and quality. \li "Windowed Sinc (Hamming)": Good interpolation quality but very time consuming. \li "Windowed Sinc (Welch)": Good interpolation quality but very time consuming. \section MAP_MAPPER_Masks Handling of masks/segmentations If you select an mask as input image, the plugin will be automatically reconfigured to settings that are suitable for the task of mapping masks. Most importantly the interpolator will be set to "nearest neighbor". */ diff --git a/Plugins/org.mitk.gui.qt.python/documentation/UserManual/QmitkPython.dox b/Plugins/org.mitk.gui.qt.python/documentation/UserManual/QmitkPython.dox index 114be980c4..0919642fc7 100644 --- a/Plugins/org.mitk.gui.qt.python/documentation/UserManual/QmitkPython.dox +++ b/Plugins/org.mitk.gui.qt.python/documentation/UserManual/QmitkPython.dox @@ -1,33 +1,33 @@ /** \page org_mitk_gui_qt_python The Python Plugin Available sections: - \ref org_mitk_gui_qt_pythonOverview - \ref org_mitk_gui_qt_pythonUsage - \ref org_mitk_gui_qt_PythonConsole - \ref org_mitk_gui_qt_PythonSnippets \section org_mitk_gui_qt_pythonOverview Overview The Python view provides the graphical front end to run Python code through the mitkPython module. Furthermore the SimpleITK/VTK/OpenCV Python wrapping can be used. Images and surfaces in the DataManager can be transferred via a drag & drop mechanism into the MITK Python Console. \section org_mitk_gui_qt_pythonUsage Transfer data -Images and surfaces can be tranferred from the data manger into the python console. To transfer an image or +Images and surfaces can be tranferred from the data manager into the python console. To transfer an image or surface simply drag it from the data manager into the Variable Stack view, as shown in Figure. A new entry will appear in the Variable Stack, as soon as the data is transferred. As soon as the entry is available the object can be accessed and modified in the python console. Three dimensional images will be copied in-memory to python via numpy and a SimpleITK image object is created with the same properties. When a two dimensional image is transferred the user can choose to transfer it as an OpenCV image object. Surfaces are fully memory mapped as a vtkPolyData object. To transfer an image or surface from the python runtime to the data manager just double click on the corresponding entry in the Variable Stack View. \imageMacro{MitkPythonPluginView.png,"Screenshot of the MITK Python Plugin",6} \section org_mitk_gui_qt_PythonConsole Console The Python console can be used for interactive programming. All items in the data storage can be accessed in the python console. The console can also be used to load python scripts and run them. \section org_mitk_gui_qt_PythonSnippets Snippets The python plugin contains some code snippets of SimpleITK/VTK/OpenCV that can be run in the python console. Snippets can be modified and saved by the user. */