diff --git a/Plugins/org.mitk.gui.qt.basicimageprocessing/documentation/UserManual/QmitkBasicImageProcessing.dox b/Plugins/org.mitk.gui.qt.basicimageprocessing/documentation/UserManual/QmitkBasicImageProcessing.dox index 6fd28a3e43..58326c13d8 100644 --- a/Plugins/org.mitk.gui.qt.basicimageprocessing/documentation/UserManual/QmitkBasicImageProcessing.dox +++ b/Plugins/org.mitk.gui.qt.basicimageprocessing/documentation/UserManual/QmitkBasicImageProcessing.dox @@ -1,132 +1,132 @@ /** -\page org_mitk_views_basicimageprocessing The Basic Image Processing Module +\page org_mitk_views_basicimageprocessing The Basic Image Processing Plugin -\image html ImageProcessing_48.png "Icon of the Module" +\image html ImageProcessing_48.png "Icon of the Plugin" \section QmitkBasicImageProcessingUserManualSummary Summary -This module provides an easy interface to fundamental image preprocessing and enhancement filters. +This view provides an easy interface to fundamental image preprocessing and enhancement filters. It offers filter operations on 3D and 4D images in the areas of noise suppression, morphological operations, edge detection and image arithmetics, as well as image inversion and downsampling. Please see \ref QmitkBasicImageProcessingUserManualDetails for more detailed information on usage and supported filters. -If you encounter problems using the module, please have a look at the \ref QmitkBasicImageProcessingUserManualTrouble page. +If you encounter problems using the view, please have a look at the \ref QmitkBasicImageProcessingUserManualTrouble page. \section QmitkBasicImageProcessingUserManualDetails Details Manual sections: - \ref QmitkBasicImageProcessingUserManualOverview - \ref QmitkBasicImageProcessingUserManualFilters - \ref QmitkBasicImageProcessingUserManualUsage - \ref QmitkBasicImageProcessingUserManualTrouble \section QmitkBasicImageProcessingUserManualOverview Overview -This module provides an easy interface to fundamental image preprocessing and image enhancement filters. +This view provides an easy interface to fundamental image preprocessing and image enhancement filters. It offers a variety of filter operations in the areas of noise suppression, morphological operations, edge detection and image arithmetics. -At the moment, the module can be used with all 3D and 4D image types loadable by MITK. 2D image support will be added in the future. +At the moment, the view can be used with all 3D and 4D image types loadable by MITK. 2D image support will be added in the future. All filters are encapsulated from the Insight Segmentation and Registration Toolkit (ITK, www.itk.org). -\image html BIP_Overview.png "MITK with the Basic Image Processing module" +\image html BIP_Overview.png "MITK with the Basic Image Processing view" -This document will tell you how to use this module, but it is assumed that you already know how to use MITK in general. +This document will tell you how to use this view, but it is assumed that you already know how to use MITK in general. \section QmitkBasicImageProcessingUserManualFilters Filters This section will not describe the fundamental functioning of the single filters in detail, though. If you want to know more about a single filter, please have a look at http://www.itk.org/Doxygen316/html/classes.html or in any good digital image processing book. For total denoising filter, please see Tony F. Chan et al., "The digital TV filter and nonlinear denoising". Available filters are:

\a Single image operations

\a Dual image operations

\section QmitkBasicImageProcessingUserManualUsage Usage All you have to do to use a filter is to: A busy cursor appeares; when it vanishes, the operation is completed. Your filtered image is displayed and selected for further processing. (If the checkbox "Hide original image" is not selected, you will maybe not see the filter result imideately, because your filtered image is possibly hidden by the original.) For two image operations, please make sure that the correct second image is selected in the drop down menu, and the image order is correct. For sure, image order only plays a role for image subtraction and division. These are conducted (Image1 - Image2) or (Image1 / Image2), respectively. Please Note: When you select a 4D image, you can select the time step for the filter to work on via the time slider at the top of the GUI. The 3D image at this time step is extracted and processed. The result will also be a 3D image. This means, a true 4D filtering is not yet supported. \section QmitkBasicImageProcessingUserManualTrouble Troubleshooting I get an error when using a filter on a 2D image.
2D images are not yet supported... I use a filter on a 4D image, and the output is 3D.
When you select a 4D image, you can select the time step for the filter to work on via the time slider at the top of the GUI. The 3D image at this time step is extracted and processed. The result will also be a 3D image. This means, a true 4D filtering is not supported by now. A filter crashes during execution.
Maybe your image is too large. Some filter operations, like derivatives, take a lot of memory. Try downsampling your image first. All other problems.
Please report to the MITK mailing list. See http://www.mitk.org/wiki/Mailinglist on how to do this. */ diff --git a/Plugins/org.mitk.gui.qt.diffusionimaging/documentation/UserManual/QmitkBrainNetworkAnalysis.dox b/Plugins/org.mitk.gui.qt.diffusionimaging/documentation/UserManual/QmitkBrainNetworkAnalysis.dox index bc4a10931b..5a754a6cc2 100644 --- a/Plugins/org.mitk.gui.qt.diffusionimaging/documentation/UserManual/QmitkBrainNetworkAnalysis.dox +++ b/Plugins/org.mitk.gui.qt.diffusionimaging/documentation/UserManual/QmitkBrainNetworkAnalysis.dox @@ -1,69 +1,69 @@ /** -\page org_mitk_views_brainnetworkanalysis The Brain Network Analysis Module +\page org_mitk_views_brainnetworkanalysis The Brain Network Analysis View -\image html QmitkBrainNetworkAnalysisViewIcon_64.png "Icon of the Module" +\image html QmitkBrainNetworkAnalysisViewIcon_64.png "Icon of the View" \section QmitkBrainNetworkAnalysisUserManualSummary Summary -This module can be used to create a network from a parcellation and a fiber image as well as to calculate and display network statistics. +This view can be used to create a network from a parcellation and a fiber image as well as to calculate and display network statistics. -This document will tell you how to use this module, but it is assumed that you already know how to use MITK in general. +This document will tell you how to use this view, but it is assumed that you already know how to use MITK in general. Please see \ref QmitkBrainNetworkAnalysisUserManualDetails for more detailed information on usage and supported filters. -If you encounter problems using the module, please have a look at the \ref QmitkBrainNetworkAnalysisUserManualTrouble page. +If you encounter problems using the view, please have a look at the \ref QmitkBrainNetworkAnalysisUserManualTrouble page. \section QmitkBrainNetworkAnalysisUserManualDetails Details Manual sections: - \ref QmitkBrainNetworkAnalysisUserManualOverview - \ref QmitkBrainNetworkAnalysisUserManualUsage - \ref QmitkBrainNetworkAnalysisUserManualTrouble \section QmitkBrainNetworkAnalysisUserManualOverview Overview -This module is currently under heavy development and as such the interface as well as the capabilities are likely to change significantly between different versions. +This view is currently under heavy development and as such the interface as well as the capabilities are likely to change significantly between different versions. This documentation describes the features of this current version. \image html QmitkBrainNetworkAnalysisInterface.png "The interface" \section QmitkBrainNetworkAnalysisUserManualUsage Usage -To create a network select first a parcellation of the brain (e.g. as provided by freesurfer ) by CTRL+Leftclick and secondly a fiber image ( as created using tractography module). Then click on the "Create Network" button. +To create a network select first a parcellation of the brain (e.g. as provided by freesurfer ) by CTRL+Leftclick and secondly a fiber image ( as created using tractography view). Then click on the "Create Network" button. To calculate network statistics select a network in the datamanager. At this time the following statistics are calculated for the entire network: Furthermore some statistics are calculated on a per node basis and displayed as histograms: Additionally you have the option to create artificial networks, for testing purposes. Currently choices are: \section QmitkBrainNetworkAnalysisUserManualTrouble Troubleshooting No known problems. All other problems.
Please report to the MITK mailing list. See http://www.mitk.org/wiki/Mailinglist on how to do this. */ diff --git a/Plugins/org.mitk.gui.qt.diffusionimaging/documentation/UserManual/QmitkTbssViewUserManual.dox b/Plugins/org.mitk.gui.qt.diffusionimaging/documentation/UserManual/QmitkTbssViewUserManual.dox index 2a199fd3a9..af6cbc7de5 100644 --- a/Plugins/org.mitk.gui.qt.diffusionimaging/documentation/UserManual/QmitkTbssViewUserManual.dox +++ b/Plugins/org.mitk.gui.qt.diffusionimaging/documentation/UserManual/QmitkTbssViewUserManual.dox @@ -1,59 +1,59 @@ /** -\page org_mitk_views_tractbasedspatialstatistics The TBSS Module +\page org_mitk_views_tractbasedspatialstatistics The TBSS View -\image html tbss.png "Icon of the Module" +\image html tbss.png "Icon of the View" \section QmitkTractbasedSpatialStatistics Summary -This module can be used to locally explore data resulting from preprocessing with the TBSS module of FSL +This view can be used to locally explore data resulting from preprocessing with the TBSS view of FSL -This document will tell you how to use this module, but it is assumed that you already know how to use MITK in general and how to work with the TBSS module of FSL. +This document will tell you how to use this view, but it is assumed that you already know how to use MITK in general and how to work with the TBSS view of FSL. -If you encounter problems using the module, please have a look at the \ref QmitkTractbasedSpatialStatisticsUserManualTrouble page. +If you encounter problems using the view, please have a look at the \ref QmitkTractbasedSpatialStatisticsUserManualTrouble page. Sections: - \ref QmitkTractbasedSpatialStatisticsUserManualOverview - \ref QmitkTractbasedSpatialStatisticsUserManualFSLImport - \ref QmitkTractbasedSpatialStatisticsUserManualRois - \ref QmitkTractbasedSpatialStatisticsUserManualProfiles - \ref QmitkTractbasedSpatialStatisticsUserManualTroubleshooting - \ref QmitkTractbasedSpatialStatisticsUserManualReferences \section QmitkTractbasedSpatialStatisticsUserManualOverview Overview -This module is currently under development and as such the interface as well as the capabilities are likely to change significantly between different versions. +This view is currently under development and as such the interface as well as the capabilities are likely to change significantly between different versions. This documentation describes the features of this current version. \section QmitkTractbasedSpatialStatisticsUserManualFSLImport FSL Import The FSL import allows to import data that has been preprocessed by FSL. FSL creates output images that typically have names like all_FA_skeletonized.nii.gz that are 4-dimensional images that contain registered images of all subjects. By loading this 4D image into the datamanager and listing the groups with the correct number of subjects, in the order of occurrence in the 4D image, in the TBSS-View using the Add button and clicking the import subject data a TBSS file is created that contains all the information needed for tract analysis. The diffusion measure of the image can be set as well. \image html fslimport.png "FSL Import" \section QmitkTractbasedSpatialStatisticsUserManualRois Regions of Interest (ROIs) To create a ROI the mean FA skeleton (typically called mean_FA_skeleton.nii.gz) that is created by FSL should be loaded in to the datamanager and selected. By using the Pointlistwidget points should be set on the skeleton (make sure to select points with relatively high FA values). Points are set by first selecting the button with the '+' and than shift-leftclick in the image. When the correct image is selected in the datamanager the Create ROI button is enabled. Clicking this will create a region of interest that passes through the previously selected points. The roi appears in the datamanager. Before doing so, the name of the roi and the information on the structure on which the ROI lies can be set. This will be saved as extra information in the roi-image. Before the ROI is calculated, a pop-up window will ask the user to provide a threshold value. This should be the same threshold that was previously used in FSL to create a binary mask of the FA skeleton. When this is not done correctly, the region of interest will possible contain zero-valued voxels. \image html tbssRoi.png "Regions of Interest (ROIs)" \section QmitkTractbasedSpatialStatisticsUserManualProfiles y selecting a tbss image with group information and a region of interest image (as was created in a previous stap). A profile plot is drawn in the plot canvas. By clicking in the graph the crosshairs jump to the corresponding location in the image. \image html profiles.png "Profile plots" \section QmitkTractbasedSpatialStatisticsUserManualTroubleshooting Troubleshooting Please report to the MITK mailing list. See http://www.mitk.org/wiki/Mailinglist on how to do this. \section QmitkTractbasedSpatialStatisticsUserManualReferences References 1. S.M. Smith, M. Jenkinson, H. Johansen-Berg, D. Rueckert, T.E. Nichols, C.E. Mackay, K.E. Watkins, O. Ciccarelli, M.Z. Cader, P.M. Matthews, and T.E.J. Behrens. Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data. NeuroImage, 31:1487-1505, 2006. 2. S.M. Smith, M. Jenkinson, M.W. Woolrich, C.F. Beckmann, T.E.J. Behrens, H. Johansen-Berg, P.R. Bannister, M. De Luca, I. Drobnjak, D.E. Flitney, R. Niazy, J. Saunders, J. Vickers, Y. Zhang, N. De Stefano, J.M. Brady, and P.M. Matthews. Advances in functional and structural MR image analysis and implementation as FSL. NeuroImage, 23(S1):208-219, 2004. */ \ No newline at end of file diff --git a/Plugins/org.mitk.gui.qt.imagecropper/documentation/UserManual/QmitkImageCropperUserManual.dox b/Plugins/org.mitk.gui.qt.imagecropper/documentation/UserManual/QmitkImageCropperUserManual.dox index 58b7015c0e..26abe156ce 100644 --- a/Plugins/org.mitk.gui.qt.imagecropper/documentation/UserManual/QmitkImageCropperUserManual.dox +++ b/Plugins/org.mitk.gui.qt.imagecropper/documentation/UserManual/QmitkImageCropperUserManual.dox @@ -1,41 +1,41 @@ /** -\page org_mitk_views_imagecropper The Image Cropper Module +\page org_mitk_views_imagecropper The Image Cropper Plugin -\image html icon.png "Icon of the Module" +\image html icon.png "Icon of the Plugin" Available sections: - \ref QmitkImageCropperUserManualOverview - \ref QmitkImageCropperUserManualFeatures - \ref QmitkImageCropperUserManualUsage - \ref QmitkImageCropperUserManualTroubleshooting \section QmitkImageCropperUserManualOverview Overview ImageCropper is a functionality which allows the user to manually crop an image by means of a bounding box. The functionality does not create a new image, it only hides parts of the original image. \section QmitkImageCropperUserManualFeatures Features - Crop a selected image using a bounding box. - Set the border voxels to a specific user defined value after cropping. \section QmitkImageCropperUserManualUsage Usage First select from the drop down menu the image to crop. The three 2D widgets show yellow rectangles representing the bounding box in each plane (axial, sagital, coronal), the lower right 3D widget shows the entire volume of the bounding box.\n - To change the size of bounding box press control + right click and move the cursor up/down or left/right in one of the three 2D views.\n - To change the orientation of the bounding box press control + middle click and move the cursor up/down or left/right in one of the three 2D views.\n - To move the bounding box press control + left click and move the cursor to the wanted position in one of the three 2D views.\n To show the result press the [crop] button.\n To crop the image again press the [New bounding box!] button.\n\n All actions can be undone by using the global undo function (Ctrl+Z).\n To set the border voxels to a specific value after cropping the image, activate the corresponding checkbox and choose a gray value. \section QmitkImageCropperUserManualTroubleshooting Troubleshooting */ diff --git a/Plugins/org.mitk.gui.qt.measurementtoolbox/documentation/UserManual/QmitkImageStatistics.dox b/Plugins/org.mitk.gui.qt.measurementtoolbox/documentation/UserManual/QmitkImageStatistics.dox index 95b83862ae..f3a1131c37 100644 --- a/Plugins/org.mitk.gui.qt.measurementtoolbox/documentation/UserManual/QmitkImageStatistics.dox +++ b/Plugins/org.mitk.gui.qt.measurementtoolbox/documentation/UserManual/QmitkImageStatistics.dox @@ -1,44 +1,44 @@ /** -\page org_mitk_views_imagestatistics The Image Statistics Module +\page org_mitk_views_imagestatistics The Image Statistics View -\image html ImageStatistic_48.png "Icon of the Module" +\image html ImageStatistic_48.png "Icon of the View" \section QmitkImageStatisticsUserManualSummary Summary -This module provides an easy interface to quickly compute some features of a whole image or a region of interest. +This view provides an easy interface to quickly compute some features of a whole image or a region of interest. -This document will tell you how to use this module, but it is assumed that you already know how to use MITK in general. +This document will tell you how to use this view, but it is assumed that you already know how to use MITK in general. Please see \ref QmitkImageStatisticsUserManualDetails for more detailed information on usage and supported filters. -If you encounter problems using the module, please have a look at the \ref QmitkImageStatisticsUserManualTrouble page. +If you encounter problems using the view, please have a look at the \ref QmitkImageStatisticsUserManualTrouble page. \section QmitkImageStatisticsUserManualDetails Details Manual sections: - \ref QmitkImageStatisticsUserManualOverview - \ref QmitkImageStatisticsUserManualUsage - \ref QmitkImageStatisticsUserManualTrouble \section QmitkImageStatisticsUserManualOverview Overview -This module provides an easy interface to quickly compute some features of a whole image or a region of interest. +This view provides an easy interface to quickly compute some features of a whole image or a region of interest. \image html Screenshot1.png "The interface" \section QmitkImageStatisticsUserManualUsage Usage -After selection of an image or a binary mask of an image in the datamanader, the Image Statistics module shows some statistical information. If a mask is selected, the name of the mask and the name of the image, to which the mask is applied, are shown at the top. +After selection of an image or a binary mask of an image in the datamanader, the Image Statistics view shows some statistical information. If a mask is selected, the name of the mask and the name of the image, to which the mask is applied, are shown at the top. Below it is the statistics window which displays the calculated statistical features (such as mean, standard deviation...) and the histogram. -At the bottom of the module are two buttons. They copy their respective data in csv format to the clipboard. +At the bottom of the view are two buttons. They copy their respective data in csv format to the clipboard. \section QmitkImageStatisticsUserManualTrouble Troubleshooting No known problems. All other problems.
Please report to the MITK mailing list. See http://www.mitk.org/wiki/Mailinglist on how to do this. */ diff --git a/Plugins/org.mitk.gui.qt.measurementtoolbox/documentation/UserManual/QmitkMeasurement.dox b/Plugins/org.mitk.gui.qt.measurementtoolbox/documentation/UserManual/QmitkMeasurement.dox index ad3e18a4d6..451a2e169f 100644 --- a/Plugins/org.mitk.gui.qt.measurementtoolbox/documentation/UserManual/QmitkMeasurement.dox +++ b/Plugins/org.mitk.gui.qt.measurementtoolbox/documentation/UserManual/QmitkMeasurement.dox @@ -1,134 +1,134 @@ /** -\page org_mitk_views_measurement The Measurement Module +\page org_mitk_views_measurement The Measurement View -\image html Measurement_48.png "Icon of the Module" +\image html Measurement_48.png "Icon of the View" \section QmitkMeasurementUserManualOverview Overview -The Measurement module enables the user to interact with 2D images or single slices of 3D image stacks and planar figure data types. It allows to measure distances, angels, pathes and several geometric figures on a dataset. +The Measurement view enables the user to interact with 2D images or single slices of 3D image stacks and planar figure data types. It allows to measure distances, angels, pathes and several geometric figures on a dataset. Available Sections: - \ref QmitkMeasurementUserManualOverview - \ref QmitkMeasurementUserManualFeatures - \ref SubOne - \ref SubTwo - \ref SubThree - \ref SubFour - \ref SubFive - \ref SubSix - \ref SubSeven - \ref QmitkMeasurementUserManualUsage - \ref One - \ref Two - \ref Three - \ref Four -The workflow to use this module is: +The workflow to use this view is: \image html Workflow.png The workflow is repeatedly useable with the same or different measurement figures, which are correlated to the choosen image and can be saved together with it for future use. On pressing the Measurement icon (see picture below the page title) in the view button line the basic appearance of the bundle is as follws. \image html Basic_Screen_edited.JPG The standard working plane is "Axial" but the other standard viewplanes ("Saggital" and "Coronal") are also valid for measurements. To swap between the view planes refer to 3M Application Bundle User Manual. \section QmitkMeasurementUserManualFeatures Features The bundle as it is depicted below offers the following features in the order of apperance on the image from top to bottom: \image html Measurement_View.JPG The first information is the selected image's name (here: DICOM-MRI-Image) followed by the measurement figures button line with the seven measurement figures. From left to right the buttons are connected with the following functions: \subsection SubOne Draw Line Draws a line between two set points and returns the distance between these points. \subsection SubTwo Draw Path Draws a path between several set points (two and more) and calculates the circumference, that is all line's length summed up. Add the final point by double left click. \subsection SubThree Draw Angle Draws two lines from three set points connected in the second set point and returns the inner angle at the second point. \subsection SubFour Draw Four Point Angle Draws two lines that may but must not intersect from four set points. The returned angle is the one depicted in the icon. \subsection SubFive Draw Circle Draws a circle by setting two points, whereas the first set point is the center and the second the radius of the circle. The measured values are the radius and the included area. \subsection SubSix Draw Rectangle Draws a rectangle by setting two points at the opposing edges of the rectangle starting with the upper left edge. The measured values are the circumference and the included area. \subsection SubSeven Draw Polygon Draws a polygon by setting three or more points. The measured values are the circumference and the included area. Add the final point by double left click. Below the buttonline the statistics window is situated, it displays the results of the actual measurements from the selected measurement figures. The content of the statistics window can be copied to the clipboard with the correspondig button for further use in a table calculation programm (e.g. Open Office Calc etc.). \image html Image_processed.JPG The last row contains again a button line to swap from the measurement bundle (activated in the image) to other supported MITK 3M3 bundles. \section QmitkMeasurementUserManualUsage Usage This Section is subdivided into four subsections:
  1. Add an image
  2. Work with measurement figures
  3. Save the image with measurement information
  4. Remove measurement figures or image
Let's start with subsection 1 \subsection One Add an image There are two possible ways to add an image to the programm. One is to grap the image with left mouse click from your prefered file browser and simply drag&drop it to the View Plane field. The other way is to use the \image html OpenButton.png button in the upper left corner of the application. A dialog window appears showing the file tree of the computer. Navigate to the wanted file and select it with the left mouse click. Afterwards just use the dialog's open button. The wanted image appears in the View Plane and in the Data Manager the images name appears as a new tree node. Now the image is loaded it can be adjusted in the usual way ( zoom in/out: right mouse button + moving the mouse up and down, moving the image: press mouse wheel and move the mouse to the wished direction, scroll through the slices( only on 3D images): scroll mouse wheel up and down). \image html Image_Loaded_Screen.JPG After the image is loaded the image's name appears in the Data Manager. By left-clicking on the image name the buttonline becomes activated. \subsection Two Work with measurement figures -The measurement module comes with seven measurement figures(see picture below), that can be applied to the images. +The measurement view comes with seven measurement figures(see picture below), that can be applied to the images. \image html MeasurementFigureButtonline.jpg The results of the measurement with each of these figures is shown in the statistics window and in the lower right corner of the view plane. \image html Image_processed_Screen.JPG When applying more then one measurement figure to the image the actual measurement figure is depicted in red and the displayed values belong to this measurement figure. All measurement figures become part of the Data Manager as a node of the image tree. \subsection Three Save the image with measurement information After applying the wanted measurement figures the entire scene consisting of the image and the measurement figures can be saved for future use. Therefore just click the right mouse button when over the image item in the Data Manager and choose the item "Save" in the opening item list. Following to that a save dialog appears where the path to the save folder can be set. Afterwards just accept your choice with the save button. \subsection Four Remove measurement figures or image If the single measurement figures or the image is not needed any longer, it can be removed solely or as an entire group. The image can't be removed without simultaneously removing all the dependent measurement figures that belong to the image tree in the Data Manager. To remove just select the wanted items in the data manager list by left-click on it or if several items wanted to be removed left click on all wanted by simultaneously holding the ctrl-button pressed. For more detailed usage of the save/remove functionality refer to the Data Manager User Manual. */ diff --git a/Plugins/org.mitk.gui.qt.measurementtoolbox/documentation/UserManual/QmitkMeasurementToolbox.dox b/Plugins/org.mitk.gui.qt.measurementtoolbox/documentation/UserManual/QmitkMeasurementToolbox.dox index 291d8d2334..e1fb8f97b2 100644 --- a/Plugins/org.mitk.gui.qt.measurementtoolbox/documentation/UserManual/QmitkMeasurementToolbox.dox +++ b/Plugins/org.mitk.gui.qt.measurementtoolbox/documentation/UserManual/QmitkMeasurementToolbox.dox @@ -1,12 +1,12 @@ /** -\page org_mitk_gui_qt_measurementtoolbox The Measurement Toolbox Bundle +\page org_mitk_gui_qt_measurementtoolbox The Measurement Toolbox Plugin \section QmitkmeasurementToolbox Manual -This bundle contains all views that provide measurement and statistics functionality. +This plugin contains all views that provide measurement and statistics functionality. */ \ No newline at end of file diff --git a/Plugins/org.mitk.gui.qt.meshdecimation/documentation/Manual/meshdecimation-manual.dox b/Plugins/org.mitk.gui.qt.meshdecimation/documentation/Manual/meshdecimation-manual.dox index 43367b70d1..5cdc4fafa6 100644 --- a/Plugins/org.mitk.gui.qt.meshdecimation/documentation/Manual/meshdecimation-manual.dox +++ b/Plugins/org.mitk.gui.qt.meshdecimation/documentation/Manual/meshdecimation-manual.dox @@ -1,33 +1,33 @@ /** -\page org_mitk_views_meshdecimation The Mesh Decimation Module +\page org_mitk_views_meshdecimation The Mesh Decimation Plugin -\image html meshdecimation.png "Icon of the Module" +\image html meshdecimation.png "Icon of the Plugin" Available sections: - \ref meshdecimationOverview - \ref meshdecimationFeatures - \ref meshdecimationUsage \section meshdecimationOverview Overview MeshDecimation is a user friendly tool to decimate a MITK surface. \section meshdecimationFeatures Features -The module offers two basic procedures to decimate surfaces: One that reduces a surface with a possible loss of topology (quality), but with a garuanteed reduction rate that is expressed in terms of percent of the original mesh. The other variant preserves the topology and stops decimating when it detects heavy topological changes. +The view offers two basic procedures to decimate surfaces: One that reduces a surface with a possible loss of topology (quality), but with a garuanteed reduction rate that is expressed in terms of percent of the original mesh. The other variant preserves the topology and stops decimating when it detects heavy topological changes. \section meshdecimationUsage Usage -\image html meshdecimation-ui.png "The user interface of the Mesh Decimation Module" +\image html meshdecimation-ui.png "The user interface of the Mesh Decimation View" -The usage of the module should be straightforward, as shown in the screenshot. To decimate a MITK surface do the following: +The usage of the view should be straightforward, as shown in the screenshot. To decimate a MITK surface do the following: - Select a surface in the datamanager - Enter a target reduction rate - Select a decimation method (\ref meshdecimationFeatures) - Press the "Decimate" button - Repeat the process until you are satisfied with the decimation - Save the surface to disk */ diff --git a/Plugins/org.mitk.gui.qt.moviemaker/documentation/UserManual/QmitkMovieMakerUserManual.dox b/Plugins/org.mitk.gui.qt.moviemaker/documentation/UserManual/QmitkMovieMakerUserManual.dox index 24068b877c..602f4243c5 100644 --- a/Plugins/org.mitk.gui.qt.moviemaker/documentation/UserManual/QmitkMovieMakerUserManual.dox +++ b/Plugins/org.mitk.gui.qt.moviemaker/documentation/UserManual/QmitkMovieMakerUserManual.dox @@ -1,45 +1,45 @@ /** -\page org_mitk_views_moviemaker The Movie Maker Module +\page org_mitk_views_moviemaker The Movie Maker View -\image html icon.png "Icon of the Module" +\image html icon.png "Icon of the View" Available sections: - \ref QmitkMovieMakerUserManualOverview - \ref QmitkMovieMakerUserManualFeatures - \ref QmitkMovieMakerUserManualUsage \section QmitkMovieMakerUserManualOverview Overview MovieMaker is a functionality for easily creating fancy movies from scenes displayed in MITK widgets. It is also possible to slide through your data, automatically rotate 3D scenes and take screenshots of widgets. \section QmitkMovieMakerUserManualFeatures Features The Movie Maker allows you to create movies and screenshots from within MITK. It can automatically scroll thorugh timesteps and slices while recording a movie. This way, you can record visualizations like a beating heart or a rotating skull. \section QmitkMovieMakerUserManualUsage Usage \image html QmitkMovieMakerControlArea.png "A view of the command area of QmitkMovieMaker" \subsection QmitkMovieMakerUserManualWindowSelection Window selection With the first two drop down boxes, you can choose which window you want to step through and which window you want to record in. Left clicking inside a window will set both drop down boxes to that window, but you can choose different windows for stepping and recording. The first drop down box defines the window along which slices will be stepped through if stepping is set to spatial (see below). The second denotes the window from which the content will be recorded. \subsection QmitkMovieMakerUserManualRecordingOptions Recording Options The slider can be used to step through the slices manually while not recording. Start and stop control a preview of what a video would look like. The buttons in the bottom part of this section can be used to create movies (windows only) or screenshots. Clicking opens a file %dialog where a name can be selected. After confirmation, a screenshot or movie is created according to the playing options. \subsection QmitkMovieMakerUserManualPlayingOptions Playing Options The first section controls whether the movie steps through slices (if a 2D view is selected), rotate the shown scene (if a 3D view is selected), or step through time steps (if set to temporal and a time resolved dataset is selected). If set to combined, a combination of both above options is used, with their speed relation set via the S/T Relation Spinbox. In the second section the direction of stepping can be set. Options are: Forward, backward and Ping-Pong, which is back-and-forth.The stepping speed can be set via the spinbox(total time in seconds). Although stepping speed is a total time in sec., this can not always be achieved. As a minimal frame rate of 25 fps is assumed to provide smooth movies, a dataset with only 25 slices will always be stepped through in 1 sec or faster. */ diff --git a/Plugins/org.mitk.gui.qt.moviemaker/documentation/UserManual/QmitkScreenshotMakerManual.dox b/Plugins/org.mitk.gui.qt.moviemaker/documentation/UserManual/QmitkScreenshotMakerManual.dox index 8536d9f771..688b614a55 100644 --- a/Plugins/org.mitk.gui.qt.moviemaker/documentation/UserManual/QmitkScreenshotMakerManual.dox +++ b/Plugins/org.mitk.gui.qt.moviemaker/documentation/UserManual/QmitkScreenshotMakerManual.dox @@ -1,19 +1,19 @@ /** \page org_mitk_views_screenshotmaker The Screenshot Maker -This module provides the functionality to create and save screenshots of the data. +This view provides the functionality to create and save screenshots of the data. Available sections: - \ref QmitkScreenshotMakerUserManualUse \image html screenshot_maker_interface.png The Screenshot Maker User Interface \section QmitkScreenshotMakerUserManualUse Usage The first section offers the option of creating a screenshot of the last activated render window (thus the one, which was last clicked into). Upon clicking the button, the Screenshot Maker asks for a filename in which the screenshot is to be stored. The multiplanar Screenshot button asks for a folder, where screenshots of the three 2D views will be stored with default names. The high resolution screenshot section works the same as the simple screenshot section, aside from the fact, that the user can choose a magnification factor. In the option section one can rotate the camera in the 3D view by using the buttons. Furthermore one can choose the background colour for the screenshots, default is black. */ diff --git a/Plugins/org.mitk.gui.qt.pointsetinteraction/documentation/UserManual/QmitkPointSetInteractionUserManual.dox b/Plugins/org.mitk.gui.qt.pointsetinteraction/documentation/UserManual/QmitkPointSetInteractionUserManual.dox index 56d10b37a8..5151fea9ac 100644 --- a/Plugins/org.mitk.gui.qt.pointsetinteraction/documentation/UserManual/QmitkPointSetInteractionUserManual.dox +++ b/Plugins/org.mitk.gui.qt.pointsetinteraction/documentation/UserManual/QmitkPointSetInteractionUserManual.dox @@ -1,38 +1,38 @@ /** -\page org_mitk_views_pointsetinteraction The Point Set Interaction Module +\page org_mitk_views_pointsetinteraction The Point Set Interaction View -\image html pointset_interaction.png "Icon of the Module" +\image html pointset_interaction.png "Icon of the View" Available sections: - \ref QmitkPointSetInteractionUserManualOverview - \ref QmitkPointSetInteractionUserManualDetails \section QmitkPointSetInteractionUserManualOverview Overview This functionality allows you to define multiple sets of points, to fill them with points and to save them in so called PointSets. \image html QmitkPointSetInteraction.png "MITK with the QmitkPointSetInteraction functionality" This document will tell you how to use this functionality, but it is assumed that you already know how to navigate through the slices of an image using the four window view. Please read the application manual for more information. \section QmitkPointSetInteractionUserManualDetails Details First of all you have to select a PointSet to use this functionality. Therefore, you have to select the point set in the data manager. If there are currently no point sets in the data tree, you have to first add a new point set to the data tree. This is done by clicking the "Add pointset..." button. \image html AddPointSet.png "The Add pointset... dialog" In the pop-up dialog, you have to specify a name for the new point set. This is also the node for the new data tree item. \image html CurrentPointSetArea.png "The Current pointset area" The "Current pointset" area contains a list of points. Within this area, all points for the current point set node are listed. To set points you have to toggle the "Set Points" button, the leftmost of the four buttons on the bottom of the view. Points can be defined by performing a left mouse button click while holding the "Shift"-key pressed in the four window view. To erase all points from the list press the next button. The user is prompted to confirm the decision. If you want to delete only a single point, left click on it in the list and then press delete on your keyboard. With the third button, a previously saved point set can be loaded and all of its points are shown in the list and the four window view. The user is prompted to select the file to be loaded. The file extension is ".mps". On the right of this button is the save button. With this function the entire point set can be saved to the harddrive. The user is prompted to select a filename. Pointsets are saved in XML fileformat but have to have a ".mps" file extension. You can select points in the render window, if the "Set Points" button is toggled, with a left mouse button click on them. If you keep the mouse button pressed, you can move the points by moving the mouse and then releasing the mouse button. With the delete key you can remove the selected points. */ \ No newline at end of file diff --git a/Plugins/org.mitk.gui.qt.registration/documentation/UserManual/QmitkDeformableRegistrationUserManual.dox b/Plugins/org.mitk.gui.qt.registration/documentation/UserManual/QmitkDeformableRegistrationUserManual.dox index 9e88fa396e..fd11c761dc 100644 --- a/Plugins/org.mitk.gui.qt.registration/documentation/UserManual/QmitkDeformableRegistrationUserManual.dox +++ b/Plugins/org.mitk.gui.qt.registration/documentation/UserManual/QmitkDeformableRegistrationUserManual.dox @@ -1,52 +1,52 @@ /** -\page org_mitk_views_deformableregistration The Deformable Image Registration Module +\page org_mitk_views_deformableregistration The Deformable Image Registration View Available sections: - \ref DeformableRegistrationUserManualOverview - \ref DeformableRegistrationUserManualDetails \section DeformableRegistrationUserManualOverview Overview -This module allows you to register 2D as well as 3D images in a deformable manner. Register means to align two images, so that they become as similar as +This view allows you to register 2D as well as 3D images in a deformable manner. Register means to align two images, so that they become as similar as possible. Registration results will directly be applied to the Moving Image. -\image html QmitkDeformableRegistration_small.png "MITK with the DeformableRegistration module" +\image html QmitkDeformableRegistration_small.png "MITK with the DeformableRegistration view" -This document will tell you how to use this module, but it is assumed that you already know how to navigate through the slices of an image using the +This document will tell you how to use this view, but it is assumed that you already know how to navigate through the slices of an image using the multi-widget. \section DeformableRegistrationUserManualDetails Details First of all you have to open the data sets which you want to register and select them in the Data Manager. You have to select exactly 2 images for registration. The image which was selected first will become the fixed image, the other one the moving image. The two selected images will remain for registration until exactly two images were selected in the Data Manager again. While -there aren't two images for registration a message is viewed on top of the module saying that registration needs two images. If two images are selected the message disappears and the interaction +there aren't two images for registration a message is viewed on top of the view saying that registration needs two images. If two images are selected the message disappears and the interaction areas for the fixed and moving data appears. On default only the fixed and moving image are shown in the render windows. If you want to have other images visible you have to set the visibility via the Data Manager. Also if you want to perform a reinit on a specific node or a global reinit for all nodes you have to use the Data Manager. \image html ImageSelectionDeformable.png "The Image area" The upper area is the "Image" area, where the selected images are shown. It is used for changing the colour of the images between grey values and red/green as well as for changing the opacity of the moving image. To do so, just use the "Moving Image Opacity:" slider. In the "Show Images Red/Green" you can switch the color from both datasets. If you check the box, the fixed dataset will be displayed in redvalues and the moving dataset in greenvalues to improve visibility of differences in the datasets. If you uncheck the "Show Images Red/Green" checkbox, both datasets will be displayed in greyvalues. \image html RegistrationDeformable.png "The Registration area for Demons based registration" In the "Registration" area you have the choice between different Demonsbased deformable registration algorithms. There are available: \li Demons Registration \li Symmetric Forces Demons Registration For both methods you have to define the same set of parameters. First you have to decide whether you want to perform a histogram matching. This can be done by selecting "Use Histogram Matching". When it is selected the corresponding parameters are enabled and have to be set. These are the "Number of Histogram Levels", "Number of Match Points" and whether to use a "Threshold at Mean Intensity". For the registration method itself you have to specify the "Number of Iterations" and the "Standard Deviation" within the "Demons Registration" area. If all this is done, you can perform the registration by clicking the "Calculate Transformation" button. Finally, you will be asked where you want the result image and the resulting deformation field to be saved. Therefore you have to select the folder and enter a filename. The results will be added in the DataStorage and can be saved in the Data Manager. */ diff --git a/Plugins/org.mitk.gui.qt.registration/documentation/UserManual/QmitkPointBasedRegistrationUserManual.dox b/Plugins/org.mitk.gui.qt.registration/documentation/UserManual/QmitkPointBasedRegistrationUserManual.dox index ab8841cd4b..cfc7e3be68 100644 --- a/Plugins/org.mitk.gui.qt.registration/documentation/UserManual/QmitkPointBasedRegistrationUserManual.dox +++ b/Plugins/org.mitk.gui.qt.registration/documentation/UserManual/QmitkPointBasedRegistrationUserManual.dox @@ -1,106 +1,106 @@ /** -\page org_mitk_views_pointbasedregistration The Point Based Registration Module +\page org_mitk_views_pointbasedregistration The Point Based Registration View -\image html pointBasedIcon.png "Icon of the Module" +\image html pointBasedIcon.png "Icon of the View" Available sections: - \ref PointBasedRegistrationUserManualOverview - \ref PointBasedRegistrationUserManualDetails \section PointBasedRegistrationUserManualOverview Overview -This module allows you to register two datasets in a rigid and deformable manner via corresponding +This view allows you to register two datasets in a rigid and deformable manner via corresponding PointSets. Register means to align two datasets, so that they become as similar as possible. Therefore you have to set corresponding points in both datasets, which will be matched. The movement, which has to be performed on the points to align them, will be performed on the moving data as well. The result is shown in the multi-widget. -\image html PointBasedRegistration_small.png "MITK with the PointBasedRegistration module" +\image html PointBasedRegistration_small.png "MITK with the PointBasedRegistration view" -This document will tell you how to use this module, but it is assumed that you already know how to navigate through +This document will tell you how to use this view, but it is assumed that you already know how to navigate through the slices of a dataset using the multi-widget. \section PointBasedRegistrationUserManualDetails Details First of all you have to open the data sets which you want to register and select them in the Data Manager. You have to select exactly 2 images for registration. The image which was selected first will become the fixed image, the other one the moving image. The two selected images will remain for registration until exactly two images were selected in the Data Manager again. While -there aren't two images for registration a message is viewed on top of the module saying that registration needs two images. If two images are selected the message disappears and the interaction +there aren't two images for registration a message is viewed on top of the view saying that registration needs two images. If two images are selected the message disappears and the interaction areas for the fixed and moving data appears. The upper area is for interaction with the fixed data. Beneath this area is the interaction area for the moving data. On default only the fixed and moving image with their corresponding pointsets are shown in the render windows. If you want to have other images visible you have to set the visibility via the Data Manager. Also if you want to perform a reinit on a specific node or a global reinit for all nodes you have to use the Data Manager. \image html FixedDataPointBased.png "The Fixed Data area" The "Fixed Data" area contains a QmitkPointListWidget. Within this widget, all points for the fixed data are listed. The label above this list shows the number of points that are already set. To set points you have to toggle the "Set Points" button, the leftmost under the QmitkPointListWidget. The views in the QmitkStdMultiWidget were reinitialized to the fixed data. Points can be defined by performing a left click while holding the "Shift"-key pressed in the QmitkStdMultiWidget. You can remove the interactor which listens for left clicks while holding the "Shift"-key pressed by detoggle the "Set Points" button. The next button, "Clear Point Set", is for deleting all specified points from this dataset. The user is prompted to confirm the decision. With the most right button, a previously saved point set can be loaded and all of its points are shown in the QmitkPointListWidget and in the QmitkStdMultiWidget. The user is prompted to select the file to be loaded. The file extension is ".mps". On the left of this button is the save button. With this function all points specified for this dataset and shown in the QmitkPointListWidget are saved to harddisk. The user is prompted to select a filename. Pointsets were saved in XML fileformat but have to have a ".mps" file extension. You can select landmarks in the render window with a left mouse button click on them. If you keep the mouse button pressed you can move the landmark to an other position by moving the mouse and then release the mouse button. With the delete key you can remove the selected landmarks. You can also select landmarks by a double click on a landmark within the QmitkPointListWidget. Using the "Up-Arrow"-button or the "F2" key you can easily move a landmark upwards and bring it further downwards by pressing "F3" or using the "Down-Arrow"-button. Thus the landmark number can be changed. The QmitkStdMultiWidget changes its view to show the position of the landmark. \image html MovingDataPointBased.png "The Moving Data area" The "Moving Data" area contains a QmitkPointListWidget. Within this widget, all points for the moving data are listed. The label above this list shows the number of points that are already set. To set points you have to toggle the "Set Points" button, the leftmost under the QmitkPointListWidget. The views in the QmitkStdMultiWidget were reinitialized to the moving data. With the "Opacity:" slider you can change the opacity of the moving dataset. If the slider is leftmost the moving dataset is totally transparent, whereas if it is rightmost the moving dataset is totally opaque. Points can be defined by performing a left click while holding the "Shift"-key pressed in the QmitkStdMultiWidget. You can remove the interactor which listens for left mousebutton click while holding the "Shift"-key pressed by detoggle the "Set Points" button. The next button, "Clear Point Set", is for deleting all specified points from this dataset. The user is prompted to confirm the decision. With the button on your right hand side, a previously saved point set can be loaded and all of its points are shown in the QmitkPointListWidget and in the QmitkStdMultiWidget. The user is prompted to select the file to be loaded. The file extension is ".mps". On the left of this button is the save button. With this function all points specified for this dataset and shown in the QmitkPointListWidget are saved to harddisk. The user is prompted to select a filename. Pointsets were saved in XML fileformat but have to have a ".mps" file extension. You can select landmarks in the render window with a left click on them. If you keep the mouse button pressed you can move the landmark to an other position by moving the mouse and then release the mouse button. With the delete key you can remove the selected landmarks. You can also select landmarks by a double click on a landmark within the QmitkPointListWidget. Using the "Up-Arrow"-button or the "F2" key you can easily move a landmark upwards and bring it further downwards by pressing "F3" or using the "Down-Arrow"-button. Thus the landmark number can be changed.The QmitkStdMultiWidget changes its view to show the position of the landmark. \image html DisplayOptionsPointBased.png "The Display Options area" In this area you can find the "Show Images Red/Green" checkbox. Here you can switch the color from both datasets. If you check the box, the fixed dataset will be displayed in redvalues and the moving dataset in greenvalues to improve visibility of differences in the datasets. If you uncheck the "Show Images Red/Green" checkbox, both datasets will be displayed in greyvalues. Before you perform your transformation it is useful to see both images again. Therefore detoggle the "Set Points" button for the fixed data as well as for the moving data. \image html RegistrationPointBased.png "The Registration area" The functions concerning the registration are displayed in the "Registration" area. It not only contains the registration method selection and the registration itself but also offers the possibility to save, undo or redo the results. Furthermore a display is implemented, which shows you how good the landmarks correspond. Those features will be explained in following paragraphs. Using the "Method"-selector, you can pick one of those transformations: Rigid, Similarity, Affine and LandmarkWarping. Depending on which one you chose, an additional specifier, "Use ICP" can be set, which leads to the following possibilities for registration: \li Rigid with ICP means only translation and rotation. The order of your landmarks will not be taken into account. E. g. landmark one in the fixed data can be mapped on landmark three in the moving data. You have to set at least one landmark in each dataset to enable the Register button which performs the transformation. \li Similarity with ICP means only translation, scaling and rotation. The order of your landmarks will not be taken into account. E. g. landmark one in the fixed data can be mapped on landmark three in the moving data. You have to set at least one landmark in each dataset to enable the Register button which performs the transformation. \li Affine with ICP means only translation, scaling, rotation and shearing. The order of your landmarks will not be taken into account. E. g. landmark one in the fixed data can be mapped on landmark three in the moving data. You have to set at least one landmark in each dataset to enable the Register button which performs the transformation. \li Rigid means only translation and rotation. The order of your landmarks will be taken into account. E. g. landmark one in the fixed data will be mapped on landmark one in the moving data. You have to set at least one landmark and the same number of landmarks in each dataset to enable the Register button which performs the transformation. \li Similarity means only translation, scaling and rotation. The order of your landmarks will be taken into account. E. g. landmark one in the fixed data will be mapped on landmark one in the moving data. You have to set at least one landmark and the same number of landmarks in each dataset to enable the Register button which performs the transformation. \li Affine means only translation, scaling, rotation and shearing. The order of your landmarks will be taken into account. E. g. landmark one in the fixed data will be mapped on landmark one in the moving data. You have to set at least one landmark and the same number of landmarks in each dataset to enable the Register button which performs the transformation. \li LandmarkWarping means a freeform deformation of the moving image, so that afterwards the landmarks are exactly aligned. The order of your landmarks will be taken into account. E. g. landmark one in the fixed data will be mapped on landmark one in the moving data. You have to set at least one landmark and the same number of landmarks in each dataset to enable the Register button which performs the transformation. The root mean squares difference between the landmarks will be displayed as number, so that you can check how good the landmarks correspond. The "Undo Transformation" button becomes enabled after performing a transformation and allows you to undo it. After doing this, the "Redo Transformation" button is enabled and lets you redo, the just undone transformation(no calculation needed) Saving of the transformed image can be done via the Data Manager. */ diff --git a/Plugins/org.mitk.gui.qt.registration/documentation/UserManual/QmitkRigidRegistrationUserManual.dox b/Plugins/org.mitk.gui.qt.registration/documentation/UserManual/QmitkRigidRegistrationUserManual.dox index 089cd17e3a..3d0c69fe8a 100644 --- a/Plugins/org.mitk.gui.qt.registration/documentation/UserManual/QmitkRigidRegistrationUserManual.dox +++ b/Plugins/org.mitk.gui.qt.registration/documentation/UserManual/QmitkRigidRegistrationUserManual.dox @@ -1,214 +1,214 @@ /** -\page org_mitk_views_rigidregistration The Rigid Registration Module +\page org_mitk_views_rigidregistration The Rigid Registration View -\image html rigidRegistrationIcon.png "Icon of the Module" +\image html rigidRegistrationIcon.png "Icon of the View" Available sections: - \ref QmitkRigidRegistrationUserManualOverview - \ref QmitkRigidRegistrationUserManualIssues - \ref QmitkRigidRegistrationUserManualDetails - \ref QmitkRigidRegistrationUserManualReferences \section QmitkRigidRegistrationUserManualOverview Overview -This module allows you to register 2D as well as 3D images in a rigid manner. If the Moving Image is an image with multiple timesteps you can select one timestep for registration. +This view allows you to register 2D as well as 3D images in a rigid manner. If the Moving Image is an image with multiple timesteps you can select one timestep for registration. Register means to align two images, so that they become as similar as possible. Therefore you can select from different transforms, metrics and optimizers. Registration results will directly be applied to the Moving Image. Also binary images as image masks can be used to restrict the metric evaluation only to the masked area. -\image html RigidRegistration_small.png "MITK with the QmitkRigidRegistration module" +\image html RigidRegistration_small.png "MITK with the QmitkRigidRegistration view" -This document will tell you how to use this module, but it is assumed that you already know how to navigate through the slices of an image using the +This document will tell you how to use this view, but it is assumed that you already know how to navigate through the slices of an image using the multi-widget. \section QmitkRigidRegistrationUserManualIssues Known Issues Depending on your system the registration can fail to allocate memory for calculating the gradient image for registration. In this case you can try to select another optimizer which is not based on a gradient image and uncheck the checkbox for "Compute Gradient". \section QmitkRigidRegistrationUserManualDetails Details First of all you have to open the data sets which you want to register and select them in the Data Manager. You have to select exactly 2 images for registration. The image which was selected first will become the fixed image, the other one the moving image. The two selected images will remain for registration until exactly two images were selected in the Data Manager again. \image html ImageArea.png "The Image area" -While there aren't two images for registration a message is viewed on top of the module saying that registration needs two images. If two images are selected the message disappears and the +While there aren't two images for registration a message is viewed on top of the view saying that registration needs two images. If two images are selected the message disappears and the interaction areas for the fixed and moving data appears. If both selected images have a binary image as childnode a selection box appears which allows, when checked, to use the binary images as image mask to restrict the registration on this certain area. If an image has more than one binary image as child, the upper one from the DataManager list is used. If the Moving Image is a dynamic images with several timesteps a slider appears to select a specific timestep for registration. On default only the fixed and moving image are shown in the render windows. If you want to have other images visible you have to set the visibility via the Data Manager. Also if you want to perform a reinit on a specific node or a global reinit for all nodes you have to use the Data Manager. The colour of the images can be changed between grey values and red/green and the opacity of the moving image can be changed. With the "Moving Image Opacity:" slider you can change the opacity of the moving dataset. In the "Show Images Red/Green" you can switch the color from both datasets. If you check the box, the fixed dataset will be displayed in red-values and the moving dataset in green-values to improve visibility of differences in the datasets. If you uncheck the "Show Images Red/Green" checkbox, both datasets will be displayed in grey-values. \image html RegistrationArea.png "The Registration area" In the "Register" area you can start the registration by clicking the "Calculate Transform" button. The optimizer value for every iteration step is diplayed as LCD number next to the "Optimizer Value:" label. Many of the registration methods can be canceled during their iteration steps by clicking the "Stop Optimization" button. During the calculation, a progress bar indicates the progress of the registration process. The render widgets are updated for every single iteration step, so that the user has the chance to supervise how good the registration process works with the selected methods and parameters. If the registration process does not lead to a sufficient result, it is possible to undo the transformation and restart the registration process with some changes in parameters. The differences in transformation due to the changed parameters can be seen in every iteration step and help the user understand the parameters. Also the optimizer value is updated for every single iteration step and shown in the GUI. The optimizer value is an indicator for the misalignment between the two images. The real time visualization of the registration as well as the optimizer value provides the user with information to trace the improvement through the optimization process. The "Undo Transformation" button becomes enabled when you have performed an transformation and you can undo the performed transformations. The "Redo Transformation" button becomes enabled when you have performed an undo to redo the transformation without to recalculate it. \image html ManualRegistrationArea.png "The Manual Registration area" In the "Manual Registration" area, shown by checking the checkbox Manual Registration, you can manually allign the images by moving sliders for translation and scaling in x-, y- and z-axis as well as for rotation around the x-, y- and z-Axis. Additionally you can automatically allign the image centers with the button "Automatic Allign Image Centers". \image html Tab2.png "The Advanced Mode tab" In the "Advanced Mode" tab you can choose a transform, a metric, an optimizer and an interpolator and you have to set the corresponding parameters to specify the registration method you want to perform. With the topmost button you can also load testpresets. These presets contain all parametersets which were saved using the "Save as Testpreset" button. The "Save as Preset" button makes the preset available from the "Automatic Registration" tab. This button should be used when a preset is not intended for finding good parameters anymore but can be used as standard preset. To show the current transform and its parameters for the registration process, the Transform checkbox has to be checked. Currently, the following transforms are implemented (for detailed information see [1] and [2]): \li Translation: Transformation by a simple translation for every dimension. \li Scale: Transformation by a certain scale factor for each dimension. \li ScaleLogarithmic: Transformation by a certain scale factor for each dimension. The parameter factors are passed as logarithms. \li Affine: Represents an affine transform composed of rotation, scaling, shearing and translation. \li FixedCenterOfRotationAffine: Represents an affine transform composed of rotation around a user provided center, scaling, shearing and translation. \li Rigid3D: Represents a 3D rotation followed by a 3D translation. \li Euler3D: Represents a rigid rotation in 3D space. That is, a rotation followed by a 3D translation. \li CenteredEuler3D: Represents a rigid rotation in 3D space around a user provided center. That is, a rotation followed by a 3D translation. \li QuaternionRigid: Represents a 3D rotation and a 3D translation. The rotation is specified as a quaternion. \li Versor: Represents a 3D rotation. The rotation is specified by a versor or unit quaternion. \li VersorRigid3D: Represents a 3D rotation and a 3D translation. The rotation is specified by a versor or unit quaternion. \li ScaleSkewVersor3D: Represents a 3D translation, scaling, shearing and rotation. The rotation is specified by a versor or unit quaternion. \li Similarity3D: Represents a 3D rotation, a 3D translation and homogeneous scaling. \li Rigid2D: Represents a 2D rotation followed by a 2D translation. \li CenteredRigid2D: Represents a 2D rotation around a user provided center followed by a 2D translation. \li Euler2D: Represents a 2D rotation and a 2D translation. \li Similarity2D: Represents a 2D rotation, homogeneous scaling and a 2D translation. \li CenteredSimilarity2D: Represents a 2D rotation around a user provided center, homogeneous scaling and a 2D translation. The desired transform can be chosen from a combo box. All parameters defining the selected transform have to be specified within the line edits and checkboxes underneath the transform combo box. To show the current metric and its parameters for the registration process, the Metric checkbox has to be checked. Currently, the following metrics are implemented (for detailed information see [1] and [2]): \li MeanSquares: Computes the mean squared pixel-wise difference in intensity between image A and B. \li NormalizedCorrelation: Computes pixel-wise cross correlation and normalizes it by the square root of the autocorrelation of the images. \li GradientDifference: Evaluates the difference in the derivatives of the moving and fixed images. \li KullbackLeiblerCompareHistogram[3]: Measures the relative entropy between two discrete probability distributions. \li CorrelationCoefficientHistogram: Computes the cross correlation coefficient between the intensities. \li MeanSquaresHistogram: The joint histogram of the fixed and the mapped moving image is built first. Then the mean squared pixel-wise difference in intensity between image A and B is calculated. \li MutualInformationHistogram: Computes the mutual information between image A and image B. \li NormalizedMutualInformationHistogram: Computes the mutual information between image A and image B. \li MattesMutualInformation[4, 5]: The method of Mattes et al. is used to compute the mutual information between two images to be registered. \li MeanReciprocalSquareDifference: Computes pixel-wise differences and adds them after passing them through a bell-shaped function 1 / (1+x^2). \li MutualInformation[6]: Computes the mutual information between image A and image B. \li MatchCardinality: Computes cardinality of the set of pixels that match exactly between the moving and fixed images. \li KappaStatistic[7]: Computes spatial intersection of two binary images. The desired metric can be chosen from a combo box. All parameters defining the selected metric have to be specified within the line edits and checkboxes underneath the metric combo box. To show the current optimizer and its parameters for the registration process, the Optimizer checkbox has to be checked. Currently, the following optimizers are implemented (for detailed information see [1] and [2]): \li Exhaustive: Fully samples a grid on the parametric space. \li GradientDescent: A simple gradient descent optimizer. \li QuaternionRigidTransformGradientDescent: Variant of a gradient descent optimizer. \li LBFGSB[8, 9]: Limited memory Broyden Fletcher Goldfarb Shannon minimization with simple bounds. \li OnePlusOneEvolutionary[10]: 1+1 evolutionary strategy. \li Powell: Implements Powell optimization using Brent line search. \li FRPR: Fletch-Reeves & Polak-Ribiere optimization using dBrent line search. \li RegularStepGradientDescent: Variant of a gradient descent optimizer. \li VersorTransform: Variant of a gradient descent optimizer. \li Amoeba: Implementation of the Nelder-Meade downhill simplex algorithm. \li ConjugateGradient: Used to solve unconstrained optimization problems. \li LBFGS: Limited memory Broyden Fletcher Goldfarb Shannon minimization. \li SPSA[11]: Based on simultaneous perturbation. \li VersorRigid3DTransform: Variant of a gradient descent optimizer for the VersorRigid3DTransform parameter space. The desired optimizer can be chosen from a combo box. All parameters defining the selected optimizer have to be specified within the line edits and checkboxes underneath the optimizer combo box. To show the current interpolator for the registration process, just check the Interpolator checkbox. Currently, the following interpolators are implemented (for detailed information see [1] and [2]): \li Linear: Intensity varies linearly between grid positions. \li NearestNeighbor: Uses the intensity of the nearest grid position. You can show and hide the parameters for the selection by checking or unchecking the corresponding area. You can save the current sets of parameters with the "Save as Testpreset" or "Save as Preset" buttons. \section QmitkRigidRegistrationUserManualReferences References: 1. L. Ibanez, W. Schroeder and K. Ng, The ITK Software Guide, Kitware Inc, New York, 2005. 2. http://www.itk.org/Doxygen/ 3. Albert C.S. Chung, William M. Wells III, Alexander Norbash, and W. Eric L. Grimson, Multi-modal Image Registration by Minimising Kullback-Leibler Distance, In Medical Image Computing and Computer-Assisted Intervention - MICCAI 2002, LNCS 2489, pp. 525 - 532. 4. D. Mattes, D. R. Haynor, H. Vesselle, T. Lewellen and W. Eubank, "Nonrigid multimodality image registration", Medical Imaging 2001: Image Processing, 2001, pp. 1609-1620. 5. D. Mattes, D. R. Haynor, H. Vesselle, T. Lewellen and W. Eubank, "PET-CT Image Registration in the Chest Using Free-form Deformations", IEEE Transactions in Medical Imaging. Vol.22, No.1, January 2003, pp.120-128. 6. Viola, P. and Wells III, W. (1997). "Alignment by Maximization of Mutual Information" International Journal of Computer Vision, 24(2):137-154. 7. AP Zijdenbos, BM Dawant, RA Margolin , AC Palmer, Morphometric analysis of white matter lesions in MR images: Method and validation, IEEE Transactions on Medical Imaging, 13(4):716-724, Dec. 1994. 8. R. H. Byrd, P. Lu and J. Nocedal. A Limited Memory Algorithm for Bound Constrained Optimization, (1995), SIAM Journal on Scientific and Statistical Computing , 16, 5, pp. 1190-1208. 9. C. Zhu, R. H. Byrd and J. Nocedal. L-BFGS-B: Algorithm 778: L-BFGS-B, FORTRAN routines for large scale bound constrained optimization (1997), ACM Transactions on Mathematical Software, Vol 23, Num. 4, pp. 550 - 560. 10. Martin Styner, G. Gerig, Christian Brechbuehler, Gabor Szekely, "Parametric estimate of intensity inhomogeneities applied to MRI", IEEE TRANSACTIONS ON MEDICAL IMAGING; 19(3), pp. 153-165, 2000. 11. Spall, J.C. (1998), "An Overview of the Simultaneous Perturbation Method for Efficient Optimization," Johns Hopkins APL Technical Digest, vol. 19, pp. 482-492. */ diff --git a/Plugins/org.mitk.gui.qt.registration/documentation/UserManual/RegistrationModuleOverview.dox b/Plugins/org.mitk.gui.qt.registration/documentation/UserManual/RegistrationModuleOverview.dox index 1f43c7a195..64aa225fa7 100644 --- a/Plugins/org.mitk.gui.qt.registration/documentation/UserManual/RegistrationModuleOverview.dox +++ b/Plugins/org.mitk.gui.qt.registration/documentation/UserManual/RegistrationModuleOverview.dox @@ -1,14 +1,14 @@ /** -\page org_mitk_gui_qt_registration The Registration Modules +\page org_mitk_gui_qt_registration The Registration Plugin \section RegistrationModuleOverviewPageOverview Overview -MITK provides several modules for the registration of images. +MITK provides several views for the registration of images. -\section RegistrationModuleOverviewPageList List of Modules +\section RegistrationModuleOverviewPageList List of Views \li \subpage org_mitk_views_deformableregistration \li \subpage org_mitk_views_pointbasedregistration \li \subpage org_mitk_views_rigidregistration */ \ No newline at end of file diff --git a/Plugins/org.mitk.gui.qt.segmentation/documentation/UserManual/org_mitk_gui_qt_segmentation.dox b/Plugins/org.mitk.gui.qt.segmentation/documentation/UserManual/org_mitk_gui_qt_segmentation.dox index 463e51d867..1947a0c348 100644 --- a/Plugins/org.mitk.gui.qt.segmentation/documentation/UserManual/org_mitk_gui_qt_segmentation.dox +++ b/Plugins/org.mitk.gui.qt.segmentation/documentation/UserManual/org_mitk_gui_qt_segmentation.dox @@ -1,292 +1,292 @@ /** -\page org_mitk_views_segmentation The Segmentation Module +\page org_mitk_views_segmentation The Segmentation Plugin -\image html segmentation.png "Icon of the Module" +\image html segmentation.png "Icon of the Plugin" Some of the features described below are not available in the open-source part of the MITK-3M3-Application. Available sections: - \ref org_mitk_gui_qt_segmentationUserManualOverview - \ref org_mitk_gui_qt_segmentationUserManualTechnical - \ref org_mitk_gui_qt_segmentationUserManualImageSelection - \ref org_mitk_gui_qt_segmentationUserManualManualKringeling - \ref org_mitk_gui_qt_segmentationUserManualManualKringeling1 - \ref org_mitk_gui_qt_segmentationUserManualManualKringeling2 - \ref org_mitk_gui_qt_segmentationUserManualManualKringeling3 - \ref org_mitk_gui_qt_segmentationUserManualManualKringeling4 - \ref org_mitk_gui_qt_segmentationUserManualManualKringeling5 - \ref org_mitk_gui_qt_segmentationUserManualOrganSegmentation - \ref org_mitk_gui_qt_segmentationUserManualOrganSegmentation1 - \ref org_mitk_gui_qt_segmentationUserManualOrganSegmentation2 - \ref org_mitk_gui_qt_segmentationUserManualOrganSegmentation99 - \ref org_mitk_gui_qt_segmentationUserManualLesionSegmentation - \ref org_mitk_gui_qt_segmentationUserManualPostprocessing - \ref org_mitk_gui_qt_segmentationUserManualSurfaceMasking - \ref org_mitk_gui_qt_segmentationUserManualTechnicalDetail \section org_mitk_gui_qt_segmentationUserManualOverview Overview The Segmentation perspective allows you to create segmentations of anatomical and pathological structures in medical images of the human body. The perspective groups a number of tools which can be used for: \image html org_mitk_gui_qt_segmentationIMGapplication.png Segmentation perspective consisting of the Data Manager view and the Segmentation view If you wonder what segmentations are good for, we shortly revisit the concept of a segmentation here. A CT or MR image is made up of volume of physical measurements (volume elements are called voxels). In CT images, for example, the gray value of each voxel corresponds to the mass absorbtion coefficient for X-rays in this voxel, which is similar in many %parts of the human body. The gray value does not contain any further information, so the computer does not know whether a given voxel is part of the body or the background, nor can it tell a brain from a liver. However, the distinction between a foreground and a background structure is required when: Creating this distinction between foreground and background is called segmentation. The Segmentation perspective of the MITK Workbench uses a voxel based approach to segmentation, i.e. each voxel of an image must be completely assigned to either foreground or background. This is in contrast to some other applications which might use an approach based on contours, where the border of a structure might cut a voxel into two %parts. The remainder of this document will summarize the features of the Segmentation perspective and how they are used. \section org_mitk_gui_qt_segmentationUserManualTechnical Technical Issues -The Segmentation perspective makes a number of assumptions. To know what this module can be used for, it will help you to know that: +The Segmentation perspective makes a number of assumptions. To know what this view can be used for, it will help you to know that: \section org_mitk_gui_qt_segmentationUserManualImageSelection Image Selection The Segmentation perspective makes use of the Data Manager view to give you an overview of all images and segmentations. \image html org_mitk_gui_qt_segmentationIMGselection.png Data Manager is used for selecting the current segmentation. The reference image is selected in the drop down box of the control area. To select the reference image (e.g. the original CT/MR image) use the drop down box in the control area of the Segmentation view. The segmentation image selected in the Data Manager is displayed below the drop down box. If no segmentation image exists or none is selected create a new segmentation image by using the "New segmentation" button. Some items of the graphical user interface might be disabled when no image is selected. In any case, the application will give you hints if a selection is needed. \section org_mitk_gui_qt_segmentationUserManualManualKringeling Manual Contouring With manual contouring you define which voxels are part of the segmentation and which are not. This allows you to create segmentations of any structeres that you may find in an image, even if they are not part of the human body. You might also use manual contouring to correct segmentations that result from sub-optimal automatic methods. The drawback of manual contouring is that you might need to define contours on many 2D slices. However, this is moderated by the interpolation feature, which will make suggestions for a segmentation. \subsection org_mitk_gui_qt_segmentationUserManualManualKringeling1 Creating New Segmentations Unless you want to edit existing segmentations, you have to create a new, empty segmentation before you can edit it. To do so, click the "New manual segmentation" button. Input fields will appear where you can choose a name for the new segmentation and a color for its display. Click the checkmark button to confirm or the X button to cancel the new segmentation. Notice that the input field suggests names once you %start typing and that it also suggests colors for known organ names. If you use names that are not yet known to the application, it will automatically remember these names and consider them the next time you create a new segmentation. Once you created a new segmentation, you can notice a new item with the "binary mask" icon in the Data Manager tree view. This item is automatically selected for you, allowing you to %start editing the new segmentation right away. \subsection org_mitk_gui_qt_segmentationUserManualManualKringeling2 Selecting Segmentations for Editing As you might want to have segmentations of multiple structures in a single patient image, the application needs to know which of them to use for editing. You select a segmenation by clicking it in the tree view of Data Manager. Note that segmentations are usually displayed as sub-items of "their" patient image. In the rare case, where you need to edit a segmentation that is not displayed as a a sub-item, you can click both the original image AND the segmentation while holding down CTRL or for Mac OS X the CMD on the keyboard. When a selection is made, the Segmentation View will hide all but the selected segmentation and the corresponding original image. When there are multiple segmentations, the unselected ones will remain in the Data Manager, you can make them visible at any time by selecting them. \subsection org_mitk_gui_qt_segmentationUserManualManualKringeling3 Selecting Editing Tools If you are familiar with the MITK Workbench, you know that clicking and moving the mouse in any of the 2D render windows will move around the crosshair that defines what part of the image is displayed. This behavior is disabled while any of the manual segmentation tools are active -- otherwise you might have a hard time concentrating on the contour you are drawing. To %start using one of the editing tools, click its button the the displayed toolbox. The selected editing tool will be active and its corresponding button will stay pressed until you click the button again. Selecting a different tool also deactivates the previous one. If you have to delineate a lot of images, you should try using shortcuts to switch tools. Just hit the first letter of each tool to activate it (A for Add, S for Subtract, etc.). \subsection org_mitk_gui_qt_segmentationUserManualManualKringeling4 Using Editing Tools All of the editing tools work by the same principle: you use the mouse (left button) to click anywhere in a 2D window (any of the orientations axial, sagittal, or frontal), move the mouse while holding the mouse button and release to finish the editing action. Multi-step undo and redo is fully supported by all editing tools. Use the application-wide undo button in the toolbar to revert erroneous %actions. \image html org_mitk_gui_qt_segmentationIMGiconAddSubtract.png Add and Subtract Tools Use the left mouse button to draw a closed contour. When releasing the mouse button, the contour will be added (Add tool) to or removed from (Subtract tool) the current segmentation. Hold down the CTRL / CMD key to invert the operation (this will switch tools temporarily to allow for quick corrections). \image html org_mitk_gui_qt_segmentationIMGiconPaintWipe.png Paint and Wipe Tools Use the slider below the toolbox to change the radius of these round paintbrush tools. Move the mouse in any 2D window and press the left button to draw or erase pixels. As the Add/Subtract tools, holding CTRL / CMD while drawing will invert the current tool's behavior. \image html org_mitk_gui_qt_segmentationIMGiconRegionGrowing.png Region Growing Tool Click at one point in a 2D slice widget to add an image region to the segmentation with the region growing tool. Moving up the cursor while holding the left mouse button widens the range for the included grey values; moving it down narrows it. When working on an image with a high range of grey values, the selection range can be influenced more strongly by moving the cursor at higher velocity. Region Growing selects all pixels around the mouse cursor that have a similar gray value as the pixel below the mouse cursor. This enables you to quickly create segmentations of structures that have a good contrast to surrounding tissue, e.g. the lungs. The tool will select more or less pixels (corresponding to a changing gray value interval width) when you move the mouse up or down while holding down the left mouse button. A common issue with region growing is the so called "leakage" which happens when the structure of interest is connected to other pixels, of similar gray values, through a narrow "bridge" at the border of the structure. The Region Growing tool comes with a "leakage detection/removal" feature. If leakage happens, you can left-click into the leakage region and the tool will try to automatically remove this region (see illustration below). \image html org_mitk_gui_qt_segmentationIMGleakage.png Leakage correction feature of the Region Growing tool
\image html org_mitk_gui_qt_segmentationIMGiconCorrection.png Correction Tool You do not have to draw a closed contour to use the Correction tool and do not need to switch between the Add and Substract tool to perform small corrective changes. The following figure shows the usage of this tool: \image html org_mitk_gui_qt_segmentationIMGcorrectionActions.png %Actions of the Correction tool illustrated.
\image html org_mitk_gui_qt_segmentationIMGiconFill.png Fill Tool Left-click inside a segmentation with holes to completely fill all holes. \image html org_mitk_gui_qt_segmentationIMGiconErase.png Erase Tool This tool removes a connected part of pixels that form a segmentation. You may use it to remove so called islands (see picture) or to clear a whole slice at once (hold CTRL while clicking). \subsection org_mitk_gui_qt_segmentationUserManualManualKringeling5 Interpolation Creating segmentations for modern CT volumes is very time-consuming, because structures of interest can easily cover a range of 50 or more slices. The Manual Segmentation View offers two helpful features for these cases:
The 3D interpolation is activated by default when using the manual segmentation tools. That means if you start contouring, from the second contour onwards, the surface of the segmented area will be interpolated based on the given contour information. The interpolation works with all available manual tools. Please note that this is currently a pure mathematical interpolation, i.e. image intensity information is not taken into account. With each further contour the interpolation result will be improved, but the more contours you provide the longer the recalculation will take. To achieve an optimal interpolation result and in this way a most accurate segmentation you should try to describe the surface with sparse contours by segmenting in arbitrary oriented planes. The 3D interpolation is not meant to be used for parallel slice-wise segmentation. \image html org_mitk_gui_qt_segmentation3DInterpolationWrongRight.png 3D Interpolation HowTo You can accept the interpolation result by clicking the "Accept" - button below the tool buttons. In this case the 3D interpolation will be deactivated automatically so that the result can be postprocessed without any interpolation running in background. During recalculation the interpolated surface is blinking yellow/white. When the interpolation has finished the surface is shown yellow with a small opacity. Additional to the surface, black contours are shown in the 3D render window. They mark the positions of all the drawn contours which were used for the interpolation. You can navigate between the drawn contours by clicking on the „Position“ - Nodes in the datamanager which are located below the selected segmentation. If you don't want to see these nodes just unckeck the „Show Position Nodes“ Checkbox and these nodes will be hidden. If you want to delete a drawn contour we recommend to use the Erase-Tool since Redo/Undo is not yet working for 3D interpolation.
The 2D Interpolation creates suggestions for a segmentation whenever you have a slice that Interpolated suggestions are displayed in a different way than manual segmentations are, until you "accept" them as part of the segmentation. To accept single slices, click the "Accept" button below the toolbox. If you have segmented a whole organ in every-x-slice, you may also review the interpolations and then accept all of them at once by clicking "... all slices". \section org_mitk_gui_qt_segmentationUserManualOrganSegmentation Organ Segmentation \note This feature is only available in our 3M3 Demo Application (http://www.mint-medical.de/productssolutions/mitk3m3/mitk3m3/#downloads) but not in the open source part of MITK The manual contouring described above is a fallback option that will work for any kind of images and structures of interest. However, manual contouring is very time-consuming and tedious. This is why a major part of image analysis research is working towards automatic segmentation methods. The Segmentation View comprises a number of easy-to-use tools for segmentation of CT images (Liver) and MR image (left ventricle and wall, left and right lung). \subsection org_mitk_gui_qt_segmentationUserManualOrganSegmentation1 Liver on CT Images On CT image volumes, preferrably with a contrast agent in the portal venous phase, the Liver tool will fully automatically analyze and segment the image. All you have to do is to load and select the image, then click the "Liver" button. During the process, which takes a minute or two, you will get visual progress feedback by means of a contour that moves closer and closer to the real liver boundaries. \subsection org_mitk_gui_qt_segmentationUserManualOrganSegmentation2 Heart, Lung, and Hippocampus on MRI While liver segmentation is performed fully automatic, the following tools for segmentation of the heart, the lungs, and the hippocampus need a minimum amount of guidance. Click one of the buttons on the "Organ segmentation" page to add an average %model of the respective organ to the image. This %model can be dragged to the right position by using the left mouse button while holding down the CTRL key. You can also use CTRL + middle mouse button to rotate or CTRL + right mouse button to scale the %model. Before starting the automatic segmentation process by clicking the "Start segmentation" button, try placing the %model closely to the organ in the MR image (in most cases, you do not need to rotate or scale the %model). During the segmentation process, a green contour that moves closer and closer to the real liver boundaries will provide you with visual feedback of the segmentation progress. The algorithms used for segmentation of the heart and lung are method which need training by a number of example images. They will not work well with other kind of images, so here is a list of the image types that were used for training: \subsection org_mitk_gui_qt_segmentationUserManualOrganSegmentation99 Other Organs As mentioned in the Heart/Lung section, most of the underlying methods are based on "training". The basic algorithm is versatile and can be applied on all kinds of segmentation problems where the structure of interest is topologically like a sphere (and not like a torus etc.). If you are interested in other organs than those offered by the current version of the Segmentation view, please contact our research team. \section org_mitk_gui_qt_segmentationUserManualLesionSegmentation Lesion Segmentation \note This feature is only available in our 3M3 Demo Application (http://www.mint-medical.de/productssolutions/mitk3m3/mitk3m3/#downloads) but not in the open source part of MITK Lesion segmentation is a little different from organ segmentation. Since lesions are not part of the healthy body, they sometimes have a diffused border, and are often found in varying places all over the body. The tools in this section offer efficient ways to create 3D segmentations of such lesions. The Segmentation View currently offers supoprt for enlarged lymph nodes. To segment an enlarged lymph node, find a more or less central slice of it, activate the "Lymph Node" tool and draw a rough contour on the inside of the lymph node. When releaseing the mouse button, a segmentation algorithm is started in a background task. The result will become visible after a couple of seconds, but you do not have to wait for it. If you need to segment several lymph nodes, you can continue to inspect the image right after closing the drawn contour. If the lymph node segmentation is not to your content, you can select the "Lymph Node Correction" tool and drag %parts of the lymph node surface towards the right position (works in 3D, not slice-by-slice). This kind of correction helps in many cases. If nothing else helps, you can still use the pure manual tools as a fallback. \section org_mitk_gui_qt_segmentationUserManualPostprocessing Things you can do with segmentations As mentioned in the introduction, segmentations are never an end in themselves. Consequently, the Segmentation view adds a couple of "post-processing" %actions to the Data Manager. These %actions are accessible through the context-menu of segmentations in Data Manager's list view \image html org_mitk_gui_qt_segmentationIMGDataManagerContextMenu.png Context menu items for segmentations. \section org_mitk_gui_qt_segmentationUserManualSurfaceMasking Surface Masking You can use the surface masking tool to create binary images from a surface which is used used as a mask on an image. This task is demonstrated below: \image html segmentationFromSurfaceBefore.png Load an image and a surface. Select the image and the surface in the corresponding drop-down boxes (both are selected automatically if there is just one image and one surface) \image html segmentationFromSurfaceAfter.png Create segmentation from surface After clicking "Create segmentation from surface" the newly created binary image is inserted in the DataManager and can be used for further processing \section org_mitk_gui_qt_segmentationUserManualTechnicalDetail Technical Information for Developers For technical specifications see \subpage QmitkSegmentationTechnicalPage and for information on the extensions of the tools system \subpage toolextensions . */ diff --git a/Plugins/org.mitk.gui.qt.volumevisualization/documentation/UserManual/QmitkVolumeVisualizationUserManual.dox b/Plugins/org.mitk.gui.qt.volumevisualization/documentation/UserManual/QmitkVolumeVisualizationUserManual.dox index 2972552f37..dbe3b81009 100644 --- a/Plugins/org.mitk.gui.qt.volumevisualization/documentation/UserManual/QmitkVolumeVisualizationUserManual.dox +++ b/Plugins/org.mitk.gui.qt.volumevisualization/documentation/UserManual/QmitkVolumeVisualizationUserManual.dox @@ -1,150 +1,150 @@ /** -\page org_mitk_views_volumevisualization The Volume Visualization Module +\page org_mitk_views_volumevisualization The Volume Visualization Plugin -\image html icon.png "Icon of the Module" +\image html icon.png "Icon of the Plugin" Available sections: \section QVV_Overview Overview -The Volume Visualization Module is a basic tool for visualizing three dimensional medical images. +The Volume Visualization Plugin is a basic tool for visualizing three dimensional medical images. MITK provides generic transfer function presets for medical CT data. These functions, that map the gray-value to color and opacity, can be interactively edited. Additionally, there are controls to quickly generate common used transfer function shapes like the threshold and bell curve to help identify a range of grey-values. \image html vroverview.png "" \section QVV_EnableVRPage Enable Volume Rendering \subsection QVV_LoadingImage Loading an image into the application Load an image into the application by Volume Visualization imposes following restrictions on images: \subsection QVV_EnableVR Enable Volumerendering \image html checkboxen.png "" Select an image in datamanager and click on the checkbox left of "Volumerendering". Please be patient, while the image is prepared for rendering, which can take up to a half minute. \subsection QVV_LODGPU The LOD & GPU checkboxes Volume Rendering requires a lot of computing resources including processor, memory and graphics card. To run volume rendering on smaller platforms, enable the LOD checkbox (level-of-detail rendering). Level-of-detail first renders a lower quality preview to increase interactivity. If the user stops to interact a normal quality rendering is issued. The GPU checkbox tries to use computing resources on the graphics card to accelerate volume rendering. It requires a powerful graphics card and OpenGL hardware support for shaders, but achieves much higher frame rates than software-rendering. \section QVV_PresetPage Applying premade presets \subsection QVV_Preset Internal presets There are some internal presets given, that can be used with normal CT data (given in Houndsfield units). A large set of medical data has been tested with that presets, but it may not suit on some special cases. Click on the "Preset" tab for using internal or custom presets. \image html mitkInternalPresets.png "" \subsection QVV_CustomPreset Saving and loading custom presets After creating or editing a transferfunction (see \ref QVV_Editing or \ref QVV_ThresholdBell), the custom transferfunction can be stored and later retrieved on the filesystem. Click "Save" (respectively "Load") button to save (load) the threshold-, color- and gradient function combined in a single .xml file. \section QVV_ThresholdBell Interactively create transferfunctions Beside the possibility to directly edit the transferfunctions (\ref QVV_Editing), a one-click generation of two commonly known shapes is given. Both generators have two parameters, that can be modified by first clicking on the cross and then moving the mouse up/down and left/right. The first parameter "center" (controlled by horizontal movement of the mouse) specifies the gravalue where the center of the shape will be located. The second parameter "width" (controlled by vertical movement of the mouse) specifies the width (or steepness) of the shape. \subsection Threshold Click on the "Threshold" tab to active the threshold function generator. \image html threshold.png "" A threshold shape begins with zero and raises to one across the "center" parameter. Lower widths results in steeper threshold functions. \subsection Bell Click on the "Bell" tab to active the threshold function generator. \image html bell.png "" A threshold shape begins with zero and raises to one at the "center" parameter and the lowers agains to zero. The "width" parameter correspondens to the width of the bell. \section QVV_Editing Customize transferfunctions in detail \subsection QVV_Navigate Choosing grayvalue interval to edit \image html slider.png "" To navigate across the grayvalue range or to zoom in some ranges use the "range"-slider. All three function editors have in common following: There are three transferfunctions to customize: \subsection QVV_GO Grayvalue -> Opacity \image html opacity.png "grayvalues will be mapped to opacity." An opacity of 0 means total transparent, an opacity of 1 means total opaque. \subsection QVV_GC Grayvalue -> Color \image html color.png "grayvalues will be mapped to color." The color transferfunction editor also allows by double-clicking a point to change its color. \subsection QVV_GGO Grayvalue and Gradient -> Opacity \image html gradient.png "" Here the influence of the gradient is controllable at specific grayvalues. */