Slicer Wiki - User contributions [en]

Documentation/3.4

2010-01-03T12:36:03Z

Jvs:

Note: This page is currently under construction

=Introduction=
[[Image:Base-Features-and-Modules.png|thumb|right|overview|[[Media:Integrating with Slicer3.ppt | Integrating with Slicer3]]]]
This page is a portal for documentation about Slicer 3.4.
For information for software developers, please go to the Developers page (see link in navigation box to the left).

=How-To Tutorials=
*[[Slicer3.4:Training|Slicer 3.4 tutorial]]
*[http://wiki.na-mic.org/Wiki/index.php/Slicer3:Training Slicer3.2 tutorial page]

=Feature Request and Problem Reports=
We have an [http://www.na-mic.org/Bug/my_view_page.php issues tracker] for Slicer 3. You need to create an account for filing reports. We keep track of both feature requests and bug reports. Make sure to use the pull-down in the upper right to select Slicer 3.
=System Requirements=
* ''Hardware:'' The hardware requirements are driven by the kind of analysis you wish to perform. For large data sets we suggest the 64 bit linux build on a machine with several gig of memory (e.g. a 1000 slice CT is half a gig of memory just to load plus there are temporary copies in memory during any processing steps). Note that Windows often does not make the full system memory available to applications.
* ''Disk Space:'' In addition to the installation directory (about 200 meg depending on platform), operations like installing downloaded extensions, caching internet data downloads, and running external programs will require additional memory; the exact amount depends on the operations you perform. To be safe, an extra gig or more of free disk space is a good idea for "typical" uses such as neuro MR analysis.
* ''Directory Settings:'' There are several user-selectable directory paths. Please confirm that these paths point to locations with sufficient storage space for your intended use.
** ''View->Application Settings->Module Settings->Temporary Directory'' is used as scratch space when running modules. By default this points to a new temp directory in your home directory.
** ''View->Application Settings->Module Settings->Extensions Install Path'' is where newly downloaded extension modules will be saved.
** ''View->Application Settings->Remote Data Handling Settings->Cache Directory'' is where downloaded data is stored for possible re-use. This defaults to the same as the Temporary Directory.

=List of Modules=
==Overview==
*The documentation on this page has been created for Slicer 3.4 and discusses the features and capabilities of menu items and panels. It is intended to be used as a live reference manual. This is a wiki. You are welcome to add to the content and improve it.
*In addition to the hundereds of smaller changes and improvements to Slicer in general, there are two substantial new addtions to Slicer 3.4:
**A new infrastructure to find and add plug-ins from a repository. See [[Documentation-3.4#Modules_for_Downloading|here]] for more information.
**A new database using XNAT desktop. See [[Documentation-3.4#XNAT_Desktop|here]] for more information.

==Main GUI==
*[[Modules:MainApplicationGUI-Documentation-3.4| Main Application GUI]] (Wendy Plesniak)
*[[Modules:EventBindings-3.4| "Hot-keys" and Keyboard Shortcuts]] (Wendy Plesniak)
*[[Modules:DataModule-3.4| Loading Scenes and Individual Datasets through the Data Module]] (W Plesniak)
*[[Modules:Loading-Data-3.4| Data Loading Details]] (Steve Pieper)
*[[Modules:Saving-Documentation-3.4| Saving Scenes and Data]] (Wendy Plesniak)
*[[Modules:SceneSnapshots-3.4| Creating and Restoring Scene Snapshots]] (Alex Yarmarkovich & Steve Pieper)
*[[Modules:ExtensionsManagementWizard-Documentation-3.4| Extensions Management Wizard]] (Terry Lorber)

==Modules==
*Please copy the template linked below, paste it into your page and customize it with your module's information.
[[Slicer3:Module_Documentation-3.4_Template|Slicer3:Module_Documentation-3.4_Template]]
*See above for info to be put into the Help and Acknowledgment Tabs
*To put your lab's logo into a module, see [[Slicer3:Execution_Model_Documentation#Adding_Module_Logos_to_Slicer3|here]] for plugin module, and [[Slicer3:Loadable_Modules:HOWTO#Adding_logo_to_your_module|here]] for loadable module.
===Core===

*[[Modules:Welcome-Documentation-3.4| Welcome Module]] (Wendy Plesniak, Steve Pieper, Sonia Pujol, Ron Kikinis)

*[[Modules:Volumes-Documentation-3.4| Volumes Module]] (Alex Yarmarkovich, Steve Pieper)
**[[Modules:Volumes:Diffusion Editor-Documentation-3.4| Diffusion Editor]] (Kerstin Kessel)
*[[Modules:Models-Documentation-3.4| Models Module]] (Alex Yarmarkovich)
*[[Modules:Fiducials-Documentation-3.4| Fiducials Module]] (Nicole Aucoin)
*[[Modules:Data-Documentation-3.4| Data Module]] (Alex Yarmarkovich)
*[[Modules:Slices-Documentation-3.4|Slices Module]] (Jim Miller)
*[[Modules:Color-Documentation-3.4| Color Module]] (Nicole Aucoin)
*[[Modules:Editor-Documentation-3.4| Interactive Editor]] (Steve Pieper)
*[[Modules:ROIModule-Documentation-3.4|ROI Module]] (Alex Yarmarkovich)
*[[Modules:VolumeRendering-Documentation-3.4| Volume Rendering Module]] (Alex Yarmarkovich)

Additional modules may appear in this section of the menu if they are not otherwise categorized by the developer.

==Specialized Modules==

Please adhere to the naming scheme for the module documentation:
*[ [Modules:MyModuleNameNoSpaces-Documentation-3.4|My Module Name With Spaces] ] (First Last Name)

*[[Modules:PETCTFusion-Documentation-3.5|PETCTFusion]] (Wendy Plesniak)

===Wizards===
*[[Modules:ChangeTracker-Documentation-3.4|ChangeTracker]] (Andriy Fedorov)
*[[Modules:IA_FEMesh-Documentation-3.4|IA FE Meshing Module]] (Vince Magnotta)
===Informatics Modules===
*[[Modules:FetchMI-Documentation-3.4| Fetch Medical Informatics Module]] (Wendy Plesniak)
*[[Modules:QDECModule-Documentation-3.4| QDEC Module]] (Nicole Aucoin)
*[[Modules:QueryAtlas-Documentation-3.4|Query Atlas Module]] (Wendy Plesniak)
===Registration===
*Overview:
**The Register Images module is an integrated solution to all your registration needs, if you want to have a resampled volume as output. It provides access to rigid, affine and b-spline itk technologies.
**The Transforms Module allows to manually align two volumes. This can be used for initial alignment.
**Linear, affine and Deformable B-Spline modules can be used stand-alone or one after the other. They can accept transformation matrices as the start pose and produce either transforms or resampled volumes as output.
**Transformation matrices derived from these modules can be used as input for resampling other volumes (including DTI) using the Resample Volume 2 module.
*[[Modules:RegisterImages-Documentation-3.4|Register Images]] (Stephen Aylward)
*[[Modules:Transforms-Documentation-3.4| Transforms Module]] (Alex Yarmarkovich)
*[[Modules:LinearRegistration-Documentation-3.4|Linear Registration]] (Daniel Blezek)
*[[Modules:AffineRegistration-Documentation-3.4|Affine Registration]] (Daniel Blezek)
*[[Modules:DeformableB-SplineRegistration-Documentation-3.4|Deformable B-Spline Registration]] (Bill Lorensen)
*[[Modules:RealignVolume-Documentation-3.4|ACPC Transform]] (Nicole Aucoin)

===Segmentation===
*[[Modules:EMSegment-Command-Line|EM Segment Command-Line]] (Brad Davis, Will Schroeder)
*[[Modules:EMSegment-Simple|EM Segment Simple]] (Brad Davis, Will Schroeder)
*[[Modules:EMSegment-TemplateBuilder|EM Segment Template Builder]] (Brad Davis, Will Schroeder)
*[[Modules:Simple Region Growing-Documentation-3.4|Simple Region Growing]] (Jim Miller)
*[[Modules:OtsuThreshold-Documentation-3.4|Otsu Threshold]] (Bill Lorensen)

===Statistics===
*[[Modules:LabelStatistics-Documentation-3.4|Label Statistics]] (Steve Pieper)

===Diffusion===
====DWI====
*Estimation
**[[Modules:DiffusionTensorEstimation-Documentation-3.4|Diffusion Tensor Estimation]] (Raul San Jose Estepar)
*[[Modules:PythonExtractBaseline-Documentation-3.4|Python Extract Baseline DWI Volume]] (Julien de Siebenthal)
*Filter
**[[Modules:JointRicianLMMSEImageFilter-Documentation-3.4|Joint Rician LMMSE Image Filter]] (Antonio Tristán Vega, Santiago Aja Fernandez)
**[[Modules:RicianLMMSEImageFilter-Documentation-3.4|Rician LMMSE Image Filter]] (Antonio Tristán Vega, Santiago Aja Fernandez, Marc Niethammer)
**[[Modules:UnbiasedNonLocalMeans-Documentation-3.4|Unbiased Non Local Means filter for DWI]] (Antonio Tristán Vega, Santiago Aja Fernandez)
*[[Modules:ShiftDWIValues-Documentation-3.4|Python Shift DWI Values]] (Julien de Siebenthal)
*[[Modules:RecenterScalar2DWI-Documentation-3.4|Python Recenter Scalar to DWI Volume]] (Julien de Siebenthal)

====DTI====
*[[Modules:ResampleDTIVolume-Documentation-3.4|Resample DTI Volume]] (Francois Budin)
*[[Modules:DiffusionTensorScalarMeasurements-Documentation-3.4 | Diffusion Tensor Scalar Measurements]] (Raul San Jose Estepar)
*Analysis

===Tractography===
*[[Modules:ROISeeding-Documentation-3.4 | Label Seeding]] (Raul San Jose Estepar)
*[[Modules:FiducialSeeding-Documentation-3.4|Fiducial Seeding]] (Alex Yarmakovich, Steve Pieper)
*[[Modules:DTIDisplay-Documentation-3.4|FiberBundles]] (Alex Yarmakovich)
*[[Modules:StochasticTractography-Documentation-3.4|Python Stochastic Tractography]] (Julien de Siebenthal)

===IGT===
*[[Modules:OpenIGTLinkIF-Documentation-3.4| OpenIGTLinkIF Module]] (Junichi Tokuda)
*[[Modules:NeuroNav-Documentation-3.4| NeuroNav Module]] (Haiying Liu)
*[[Modules:ProstateNav-Documentation-3.4| ProstateNav Module]] (Junichi Tokuda)
===Filtering===
*[[Modules:CheckerboardFilter-Documentation-3.4|Checkerboard Filter]] (Bill Lorensen)
*[[Modules:HistogramMatching-Documentation-3.4|Histogram Matching]] (Bill Lorensen)
*[[Modules:ImageLabelCombine-3.4|Image Label Combine]] (Alex Yarmarkovich)
*[[Modules:ResampleVolume-Documentation-3.4|Resample Volume]] (Bill Lorensen)
*[[Modules:ResampleVolume2-Documentation-3.4|Resample Volume2]] (Francois Budin)
*[[Modules:ThresholdImage-Documentation-3.4|Threshold Image]] (Nicole Aucoin)
*Arithmetic
**[[Modules:AddImages-Documentation-3.4|Add Images]] (Bill Lorensen)
**[[Modules:SubtractImages-Documentation-3.4|Subtract Images]] (Bill Lorensen)
**[[Modules:CastImage-Documentation-3.4|Cast Image]] (Nicole Aucoin)
*Denoising
**[[Modules:GradientAnisotropicFilter-Documentation-3.4| Gradient Anisotropic Filter]] (Bill Lorensen checked this in)
**[[Modules:CurvatureAnisotropicDiffusion-Documentation-3.4|Curvature Anisotropic Diffusion]] (Bill Lorensen)
**[[Modules:GaussianBlur-Documentation-3.4|Gaussian Blur]] (Julien Jomier, Stephen Aylward)
**[[Modules:MedianFilter-Documentation-3.4|Median Filter]] (Bill Lorensen)
*Morphology
**[[Modules:VotingBinaryHoleFilling-Documentation-3.4|Voting Binary Hole Filling]] (Bill Lorensen)
**[[Modules:GrayscaleFillHole-Documentation-3.4|Grayscale Fill Hole]] (Bill Lorensen)
**[[Modules:GrayscaleGrindPeak-Documentation-3.4|Grayscale Grind Peak]] (Bill Lorensen)

===Surface Models===
*[[Modules:Model_Maker-Documentation-3.4| Modelmaker]] (Nicole Aucoin)
*Grayscale Model Maker (Bill Lorensen)

*Freesurfer Surface Section Extraction (Katharina Quintus)
*[[Modules:PythonSurfaceConnectivity-Documentation-3.4| Python Surface Connectivity]] (Luca Antiga, Daniel Blezek)
*[[Modules:PythonSurfaceICPRegistration-Documentation-3.4| Python Surface ICP Registration]] (Luca Antiga, Daniel Blezek)
*[[Modules:PythonSurfaceToolbox-Documentation-3.4| Python Surface Toolbox]] (Luca Antiga, Daniel Blezek)
*[[Modules:ClipModel-Documentation-3.4| Clip Model]] (Alex Yarmarkovich)
*[[Slicer3:Model_Into_Label_Volume_Documentation-3.4| Model into Label Volume]] (Nicole Aucoin)

===Batch processing===
*[[Modules:EMSegmentBatch-Documentation-3.4|EM Segmenter batch]] (Julien Jomier, Brad Davis)
*[[Modules:GaussianBlurBatch-Documentation-3.4|Gaussian Blur batch]] (Julien Jomier, Stephen Aylward)
*[[Modules:RegisterImagesBatch-Documentation-3.4|Register Images batch]] (Julien Finet, Stephen Aylward)
*[[Modules:ResampleVolumeBatch-Documentation-3.4|Resample Volume batch]] (Julien Finet)

===Converters===
*[[Modules:CreateaDicomSeries-Documentation-3.4|Create a Dicom Series]] (Bill Lorensen)
*[[Modules:DicomToNRRD-3.4|Dicom to NRRD]] (Xiaodong Tao)
*[[Modules:OrientImages-Documentation-3.4|Orient Images]] (Bill Lorensen)
*[[Modules:PythonExplodeVolumeTransform-Documentation-3.4| Python Explode Volume Transform]] (Luca Antiga, Daniel Blezek)
*[[Modules:ExtractSubvolume-Documentation-3.4| Extract Subvolume]] (Steve Pieper)

===Work in Progress===
Various tools in development will appear here depending on the version of slicer you are using.
===Developer Tools===
*[[Modules:PythonScript-Documentation-3.4| Python Script]] (Luca Antiga, Daniel Blezek)
*[[Modules:PythonNumpyScript-Documentation-3.4| Python Numpy Script]] (Luca Antiga, Daniel Blezek)
*[[Modules:ExecutionModelTour-Documentation-3.4|Execution Model Tour]] (Daniel Blezek, Bill Lorensen)
*[[Modules:ScriptedModuleExample-Documentation-3.4| Scripted Module Example]] (Steve Pieper)

=Extensions for Downloading=
[[Image:SlicerOnNITRC2009.png|thumb|right|Slicer on NITRC]]
Work is in progress to create infrastructure for searching and loading extensions. See [[Slicer3:Extensions]] for more information.
*This will allow contributors and software developers to post their own Slicer extensions and have them compiled against the "official" versions of Slicer.
*Users can browse these contributed extensions and install them on their own versions of Slicer.

We are currently using NITRC as a repository for contributed extensions. As a general rule, we do not test them ourselves, it is the downloaders job to ensure that they do what they want them to do.
Click [http://www.nitrc.org/search/?type_of_search=soft&words=slicer3&Search.x=0&Search.y=0&Search=Search here] to see a listing of Slicer 3 extensions on NITRC.

[[Image:Slicer-3.4.1-extension-manager-2009-10-02.png|thumb|right|Extension manager dialog box]]
To add extension modules to an installed binary of slicer:

* Use the View->Extension Manager menu option
* The dialog will be initialized with the URL to the extensions that have been compiled to match your binary of slicer.
** '''Note''' installing extensions from a different repository URL is likely to be unstable due to platform and software version differences.
** You can select a local install directory for your downloaded extensions (be sure to choose a directory with enough free space).
* Select the extensions you wish to install and click to download them. Installed extensions will be available when you restart slicer.
* To turn modules on or off, you can use the Module Settings page of the View->Application Settings dialog.

=XNAT Desktop and FetchMI=
*Work is underway to use XNAT desktop (xnd) as a local database for Slicer. This database will exist in parallel with the other load and save mechanisms and will allow to download/upload individual files or entire scenes with all their dependent files.
*Users of Slicer will have to install xnd on their computer. Once set up, the FetchMI interface will allow users to upload and download mrml scenes with all the dependent files, or individual volumes, models, other components of slicer scenes.
*See [http://nrg.wustl.edu/xnd/download here] for a link to the download site for xnd. See [http://www.xnat.org/xnd here] for documentation on how to install XNAT desktop on your computer.
*'''On Macs and Linux you currently have to change permissions of the executable after installation.'''
*In the future (summer 2009) xnd will be able to upload and download mrml scenes to xnat enterprise.

*FetchMI is the current interface inside slicer for exploring information stored in xnd and down and upload such data. It is a "sandbox" implementation to help us understand how users will want to use remotely stored data and metadata in the Slicer environment. Eventually, FetchMI's remote load and save will be integrated with Slicer's existing load and save interfaces, and FetchMI's data tagging functionality will be more fully developed as a new metadata authoring module.
*See [[Modules:FetchMI-Documentation-3.4|here]] for more information about FETCHMI. User comments and suggestions are welcome.

=FreeSufer Integration=

* FreeSurfer surfaces and scalar overlays can be loaded via the [[Modules:Models-Documentation-3.4|Models]] module and MGZ volumes can be loaded via the File -> Add Data widget.
* More detailed information can be found [[Modules:Freesurfer-Documentation-3.4|here]].

= Requirements for modules to be added to the release=
{| border="00" cellpadding="5" cellspacing="0"
|-
| rowspan="2"|
* The module is '''feature complete''' for the tasks advertised
* The module has a '''test'''. See [http://wiki.na-mic.org/Wiki/index.php/Slicer3:Execution_Model_Testing '''here'''] for more information.
* Module has '''documentation''' on the [[Documentation-3.4#Modules|Slicer wiki]]. Please use the template provided [[Documentation-3.4#Modules|'''here''']] to structure your page.
*Please add a pointer to the documentation on the Slicer wiki to the the '''Help''' tab of the module. See the '''Editor module''' in Slicer for an example.
* The contributor (and their manager/advisor), the lab (with labs/institution logo) and the funding source (with grant number, logo optional) are listed in the '''Acknowledgment''' tab of the module. Please see the '''Models module''' for and example. The people listed in the acknowledgement will be the primary people for support and maintenance relative of the module.
** '''Style Guide:''' All acknowledgment icons should be 100x100 pixels, preferably in png format.
** '''Accessing logos:''' Icons for BIRN, NAC, NA-MIC and IGT are included in Slicer3/Base/GUI//vtkSlicerBaseAcknowledgementLogoIcons.cxx/h and resources for them are in Slicer3/Base/GUI/Resources/vtkSlicerBaseAcknowledgementLogos_ImageData.h. The API for vtkSlicerModuleGUI provides access to these icons.
** '''Adding logos:''' Please add your logos and additional image resources to the location reference above in order to promote shared use (and to prevent duplication in the code.)
| style="background: #e5e5e5" align="center"| Examples for the Help and
Acknowledgment Panels
|-
| style="background: #ebeced"|[[Image:SlicerHelpExample.png|center|200px]][[Image:SlicerAcknowledgementExample.png|center|200px]]
|}

Documentation/3.5

2010-01-03T12:33:42Z

Jvs:

=Main GUI=

==Main GUI==
*[[Modules:MainApplicationGUI-Documentation-3.5| Main Application GUI]]
*[[Modules:EventBindings-3.5| "Hot-keys" and Keyboard Shortcuts]]
*[[Modules:DataModule-3.5| Loading Scenes and Individual Datasets through the Data Module]]
*[[Modules:Loading-Data-3.5| Data Loading Details]]
*[[Modules:Saving-Documentation-3.5| Saving Scenes and Data]]
*[[Modules:SceneSnapshots-3.5| Creating and Restoring Scene Snapshots]]
*[[Modules:ExtensionsManagementWizard-Documentation-3.5| Extensions Management Wizard]] (Terry G.)

=Modules=
*Please copy the template linked below, paste it into your page and customize it with your module's information.
[[Slicer3:Module_Documentation-3.5_Template|Slicer3:Module_Documentation-3.5_Template]]
*See [[Documentation-3.5#Requirements for Modules|below]] for info to be put into the Help and Acknowledgment Tabs
*To put your lab's logo into a module, see [[Slicer3:Execution_Model_Documentation#Adding_Module_Logos_to_Slicer3|here]]

Please adhere to the naming scheme for the module documentation:
*[ [Modules:MyModuleNameNoSpaces-Documentation-3.5|My Module Name With Spaces] ] (First Last Name)

= Requirements for Modules =
{| border="00" cellpadding="5" cellspacing="0"
|-
| rowspan="2"|
* The module is '''feature complete''', it does everything that it advertises it can do
* The module has a '''test'''. See [http://wiki.na-mic.org/Wiki/index.php/Slicer3:Execution_Model_Testing '''here'''] for more information.
* Module has '''documentation''' on the [[Documentation-3.5#Modules|Slicer wiki]]. Please use the template provided [[Documentation-3.5#Modules|'''here''']] to structure your page.
*Please add a pointer to the documentation on the Slicer wiki to the the '''Help''' tab of the module. See the '''Editor module''' in Slicer for an example.
* The contributor (and their manager/advisor), the lab (with labs/institution logo) and the funding source (with grant number, logo optional) are listed in the '''Acknowledgment''' tab of the module. Please see the '''Models module''' for an example. The people listed in the acknowledgement will be the primary people for support and maintenance relative of the module.
** '''Style Guide:''' All acknowledgment icons should be 100x100 pixels, preferably in png format.
** '''Accessing logos:''' Icons for BIRN, NAC, NA-MIC and IGT are included in Slicer3/Base/GUI//vtkSlicerBaseAcknowledgementLogoIcons.cxx/h and resources for them are in Slicer3/Base/GUI/Resources/vtkSlicerBaseAcknowledgementLogos_ImageData.h. The API for vtkSlicerModuleGUI provides access to these icons.
** '''Adding logos:''' Please add additional image resources and logo icons to these files as required in order to promote shared use (and to prevent duplication in the code.)
* Many modules are better suited to be [[Documentation-3.4#Extensions_for_Downloading|downloadable extensions]]. The same module creation guidelines apply, but the actual implementation is done outside of the slicer source code repository.
| style="background: #e5e5e5" align="center"| Examples for the Help and
Acknowledgment Panels
|-
| style="background: #ebeced"|[[Image:SlicerHelpExample.png|center|200px]][[Image:SlicerAcknowledgementExample.png|center|200px]]
|}

=List of Modules new to 3.5=
* [[Modules:MRIBiasFieldCorrection-Documentation-3.5|MRI Bias Field Correction]] (Nicolas Rannou, Sylvain Jaume)
* [[Modules:FourDImage-Documentation-3.5|4D Image (Viewer)]] (Junichi Tokuda)
* [[Modules:FourDAnalysis-Documentation-3.5|4D Analysis (Time-intensity curve plotting and analysis)]] (Junichi Tokuda)
* [[Modules:FastMarchingSegmentation-Documentation-3.5|Fast Marching segmentation]] (Andriy Fedorov)
* [[Modules:GyriContourSegmentation-Documentation-3.5|Gyri Contour Segmentation]] (Peter Karasev)
* [[Modules:ExtractSubvolumeROI-Documentation-3.5|Subvolume extraction with ROI widget]] (Andriy Fedorov)
* [[Modules:RegistrationMetrics-Documentation-3.5 | Registration Metrics (HD and DSC) ]] (Haytham Elhawary)
* [[Modules:Measurements-Documentation-3.5 | Measurements (rulers and angles) ]] (Nicole Aucoin)

=List of pre-existing Modules=
===Core===
*[[Modules:Camera-Documentation-3.5| Camera Module]] (Sebastian Barre)
*[[Modules:Welcome-Documentation-3.4| Welcome Module]] (Wendy Plesniak, Steve Pieper, Sonia Pujol, Ron Kikinis)
*[[Modules:Volumes-Documentation-3.4| Volumes Module]] (Alex Yarmarkovich, Steve Pieper)
**[[Modules:Volumes:Diffusion Editor-Documentation-3.4| Diffusion Editor]] (Kerstin Kessel)
*[[Modules:Models-Documentation-3.4| Models Module]] (Alex Yarmarkovich)
*[[Modules:Fiducials-Documentation-3.4| Fiducials Module]] (Nicole Aucoin)
*[[Modules:Data-Documentation-3.4| Data Module]] (Alex Yarmarkovich)
*[[Modules:Slices-Documentation-3.4|Slices Module]] (Jim Miller)
*[[Modules:Color-Documentation-3.4| Color Module]] (Nicole Aucoin)
*[[Modules:Editor-Documentation-3.4| Interactive Editor]] (Steve Pieper)
*[[Modules:ROIModule-Documentation-3.4|ROI Module]] (Alex Yarmarkovich)
*[[Modules:VolumeRendering-Documentation-3.5| Volume Rendering Module]] (Yanling Liu, Alex Yarmarkovich)

==Specialized Modules==

Please adhere to the naming scheme for the module documentation:
*[ [Modules:MyModuleNameNoSpaces-Documentation-3.5|My Module Name With Spaces] ] (First Last Name)

===Wizards===
*[[Modules:ChangeTracker-Documentation-3.4|ChangeTracker]] (Andriy Fedorov)
*[[Modules:IA_FEMesh-Documentation-3.4|IA FE Meshing Module]] (Vince Magnotta)
===Informatics Modules===
*[[Modules:FetchMI-Documentation-3.4| Fetch Medical Informatics Module]] (Wendy Plesniak)
*[[Modules:QDECModule-Documentation-3.4| QDEC Module]] (Nicole Aucoin)
*[[Modules:QueryAtlas-Documentation-3.4|Query Atlas Module]] (Wendy Plesniak)
===Registration===
*Overview:
**The Register Images module is an integrated solution to all your registration needs, if you want to have a resampled volume as output. It provides access to rigid, affine and b-spline itk technologies.
**The Transforms Module allows to manually align two volumes. This can be used for initial alignment.
**Linear, affine and Deformable B-Spline modules can be used stand-alone or one after the other. They can accept transformation matrices as the start pose and produce either transforms or resampled volumes as output.
**Transformation matrices derived from these modules can be used as input for resampling other volumes (including DTI) using the Resample Volume 2 module.
*[[Modules:RegisterImages-Documentation-3.4|Register Images]] (Stephen Aylward)
*[[Modules:Transforms-Documentation-3.4| Transforms Module]] (Alex Yarmarkovich)
*[[Modules:LinearRegistration-Documentation-3.4|Linear Registration]] (Daniel Blezek)
*[[Modules:AffineRegistration-Documentation-3.4|Affine Registration]] (Daniel Blezek)
*[[Modules:DeformableB-SplineRegistration-Documentation-3.4|Deformable B-Spline Registration]] (Bill Lorensen)
*[[Modules:RealignVolume-Documentation-3.4|ACPC Transform]] (Nicole Aucoin)

===Segmentation===
*[[Modules:EMSegment|EM Segment]] (Sylvain Jaume, Nicolas Rannou)
*[[Modules:EMSegment-Command-Line|EM Segment Command-Line]] (Brad Davis, Will Schroeder)
*[[Modules:EMSegment-Simple|EM Segment Simple]] (Brad Davis, Will Schroeder)
*[[Modules:EMSegment-TemplateBuilder|EM Segment Template Builder]] (Brad Davis, Will Schroeder)
*[[Modules:Simple Region Growing-Documentation-3.4|Simple Region Growing]] (Jim Miller)
*[[Modules:OtsuThreshold-Documentation-3.4|Otsu Threshold]] (Bill Lorensen)

===Statistics===
*[[Modules:LabelStatistics-Documentation-3.4|Label Statistics]] (Steve Pieper)

===Diffusion===
====DWI====
*Estimation
**[[Modules:DiffusionTensorEstimation-Documentation-3.4|Diffusion Tensor Estimation]] (Raul San Jose Estepar)
*[[Modules:PythonExtractBaseline-Documentation-3.4|Python Extract Baseline DWI Volume]] (Julien de Siebenthal)
*Filter
**[[Modules:JointRicianLMMSEImageFilter-Documentation-3.4|Joint Rician LMMSE Image Filter]] (Antonio Tristán Vega, Santiago Aja Fernandez)
**[[Modules:RicianLMMSEImageFilter-Documentation-3.4|Rician LMMSE Image Filter]] (Antonio Tristán Vega, Santiago Aja Fernandez, Marc Niethammer)
**[[Modules:UnbiasedNonLocalMeans-Documentation-3.4|Unbiased Non Local Means filter for DWI]] (Antonio Tristán Vega, Santiago Aja Fernandez)
*[[Modules:ShiftDWIValues-Documentation-3.4|Python Shift DWI Values]] (Julien de Siebenthal)
*[[Modules:RecenterScalar2DWI-Documentation-3.4|Python Recenter Scalar to DWI Volume]] (Julien de Siebenthal)

====DTI====
*[[Modules:ResampleDTIVolume-Documentation-3.4|Resample DTI Volume]] (Francois Budin)
*[[Modules:DiffusionTensorScalarMeasurements-Documentation-3.4 | Diffusion Tensor Scalar Measurements]] (Raul San Jose Estepar)
*Analysis

===Tractography===
*[[Modules:ROISeeding-Documentation-3.4 | Label Seeding]] (Raul San Jose Estepar)
*[[Modules:FiducialSeeding-Documentation-3.4|Fiducial Seeding]] (Alex Yarmakovich, Steve Pieper)
*[[Modules:DTIDisplay-Documentation-3.4|FiberBundles]] (Alex Yarmakovich)
*[[Modules:StochasticTractography-Documentation-3.4|Python Stochastic Tractography]] (Julien de Siebenthal)
*[[Modules:ROISelect-Documentation-3.5|ROI Select]] (Lauren O'Donnell)

===IGT===
*[[Modules:OpenIGTLinkIF-Documentation-3.4| OpenIGTLinkIF Module]] (Junichi Tokuda)
*[[Modules:NeuroNav-Documentation-3.4| NeuroNav Module]] (Haiying Liu)
*[[Modules:ProstateNav-Documentation-3.4| ProstateNav Module]] (Junichi Tokuda)
===Filtering===
*[[Modules:CheckerboardFilter-Documentation-3.4|Checkerboard Filter]] (Bill Lorensen)
*[[Modules:HistogramMatching-Documentation-3.4|Histogram Matching]] (Bill Lorensen)
*[[Modules:ImageLabelCombine-3.4|Image Label Combine]] (Alex Yarmarkovich)
*[[Modules:ResampleVolume-Documentation-3.4|Resample Volume]] (Bill Lorensen)
*[[Modules:ResampleVolume2-Documentation-3.4|Resample Volume2]] (Francois Budin)
*[[Modules:ThresholdImage-Documentation-3.4|Threshold Image]] (Nicole Aucoin)
*Arithmetic
**[[Modules:AddImages-Documentation-3.4|Add Images]] (Bill Lorensen)
**[[Modules:SubtractImages-Documentation-3.4|Subtract Images]] (Bill Lorensen)
** [[Modules:CastImage-Documentation-3.4|Cast Image]] (Nicole Aucoin)
*Denoising
**[[Modules:GradientAnisotropicFilter-Documentation-3.4| Gradient Anisotropic Filter]] (Bill Lorensen checked this in)
**[[Modules:CurvatureAnisotropicDiffusion-Documentation-3.4|Curvature Anisotropic Diffusion]] (Bill Lorensen)
**[[Modules:GaussianBlur-Documentation-3.4|Gaussian Blur]] (Julien Jomier, Stephen Aylward)
**[[Modules:MedianFilter-Documentation-3.4|Median Filter]] (Bill Lorensen)
*Morphology
**[[Modules:VotingBinaryHoleFilling-Documentation-3.4|Voting Binary Hole Filling]] (Bill Lorensen)
**[[Modules:GrayscaleFillHole-Documentation-3.4|Grayscale Fill Hole]] (Bill Lorensen)
**[[Modules:GrayscaleGrindPeak-Documentation-3.4|Grayscale Grind Peak]] (Bill Lorensen)

===Surface Models===
*[[Modules:Model_Maker-Documentation-3.4| Modelmaker]] (Nicole Aucoin)
*Grayscale Model Maker (Bill Lorensen)

*Freesurfer Surface Section Extraction (Katharina Quintus)
*[[Modules:PythonSurfaceConnectivity-Documentation-3.4| Python Surface Connectivity]] (Luca Antiga, Daniel Blezek)
*[[Modules:PythonSurfaceICPRegistration-Documentation-3.4| Python Surface ICP Registration]] (Luca Antiga, Daniel Blezek)
*[[Modules:PythonSurfaceToolbox-Documentation-3.4| Python Surface Toolbox]] (Luca Antiga, Daniel Blezek)
*[[Modules:ClipModel-Documentation-3.4| Clip Model]] (Alex Yarmarkovich)
*[[Slicer3:Model_Into_Label_Volume_Documentation-3.4| Model into Label Volume]] (Nicole Aucoin)

===Batch processing===
*[[Modules:EMSegmentBatch-Documentation-3.4|EM Segmenter batch]] (Julien Jomier, Brad Davis)
*[[Modules:GaussianBlurBatch-Documentation-3.4|Gaussian Blur batch]] (Julien Jomier, Stephen Aylward)
*[[Modules:RegisterImagesBatch-Documentation-3.4|Register Images batch]] (Julien Finet, Stephen Aylward)
*[[Modules:ResampleVolumeBatch-Documentation-3.4|Resample Volume batch]] (Julien Finet)

===Converters===
*[[Modules:CreateaDicomSeries-Documentation-3.4|Create a Dicom Series]] (Bill Lorensen)
*[[Modules:DicomToNRRD-3.4|Dicom to NRRD]] (Xiaodong Tao)
*[[Modules:OrientImages-Documentation-3.4|Orient Images]] (Bill Lorensen)
*[[Modules:PythonExplodeVolumeTransform-Documentation-3.4| Python Explode Volume Transform]] (Luca Antiga, Daniel Blezek)
*[[Modules:ExtractSubvolume-Documentation-3.4| Extract Subvolume]] (Steve Pieper)

=Slicer Extensions=

==Extensions for Downloading==
===Introduction===
[[Image:SlicerOnNITRC2009.png|thumb|right|Slicer on NITRC]]
* Slicer Extensions are a mechanism for third parties to provide modules which extend the functionality of 3d Slicer.
* Some of the extensions do not use the Slicer license. Please review carefully.
* For a subset of extensions, you can use the extension wizard in Slicer to find their webpages and to install/uninstall individual extensions. In case of problems with those modules, please talk directly to the developers of the extensions.
* The version that is available through the extension manager is chosen by the developer of that extension

We are using NITRC as the primary repository for contributed extensions. As a general rule, we do not test the extensions ourselves. Use them at your own risk.
Click [http://www.nitrc.org/search/?type_of_search=soft&words=slicer3&Search.x=0&Search.y=0&Search=Search here] to see a listing of Slicer 3 extensions on NITRC.

[[Image:Slicer-3.4.1-extension-manager-2009-10-02.png|thumb|right|Extension manager dialog box]]
To add extension modules to an installed binary of slicer:
* Use the View->Extension Manager menu option
* The dialog will be initialized with the URL to the extensions that have been compiled to match your binary of slicer.
** '''Note''' installing extensions from a different repository URL is likely to be unstable due to platform and software version differences.
** You can select a local install directory for your downloaded extensions (be sure to choose a directory with enough free space).
* Select the extensions you wish to install and click to download them. Installed extensions will be available when you restart slicer.
* To turn modules on or off, you can use the Module Settings page of the View->Application Settings dialog.

*Extensions are compiled as part of the nightly build. In order to have your extension compiled nightly and made available to end users, please contact the Slicer team. For explanations for developers see [[Slicer3:Extensions| here]]

'''Installation'''
*Click on the icon to start the extensions wizard
[[image:ExtensionsWizard.png|Extensions Wizard]]

===Listing of available plug-ins===
* VMTK (Daniel Haehn)
**You need to install the [[Modules:VMTKSlicerModule|VmtkSlicerModule]] to run any of the other three.
**[[Modules:VMTKEasyLevelSetSegmentation|VMTKEasyLevelSetSegmentation]] - providing level-set segmentation of vessels, aneurysms and tubular structures using an easy interface
**[[Modules:VMTKLevelSetSegmentation|VMTKLevelSetSegmentation]] - providing level-set segmentation of vessels, aneurysms and tubular structures using different algorithms
**[[Modules:VMTKVesselEnhancement|VMTKVesselEnhancement]] - providing vessel enhancement filters to highlight vasculature or tubular structures

* [[Modules:EMDTIClustering-Documentation-3.5|EM DTI Clustering]] (Mahnaz Maddah)

* [[Modules:LabelDiameterEstimation-Documentation-3.5|Label Diameter Estimation]] (Andriy Fedorov)

===Extensions Contact List===
This is a first pass list of extension authors; more to come!

*EMFiberClusteringModule Mahnaz Maddah maddah @nospam@ ge.com
*BRAINSROIAuto Greg Harris gregory-harris @nospam@ uiowa.edu
*Bubble Maker Carlos Mendoza carlos.sanchez.medoza @nospam@ gmail.com
*Hammer Registration Dinggang Shen dgshen @nospam@ med.unc.edu
*Lupus Lesion Mark Scully mscully @nospam@ mrn.org
*VmtkSlicerModule Daniel Haehn haehn @nospam@ bwh.harvard.edu
*Vmtkin3DSlicer Daniel Haehn
*BRAINSFit Eun Young Kim eunyoung-kim @nospam@ uiowa.edu
*ARCTIC Cedric Mathieu ced.mathieu @nospam@ gmail.com

Slicer3:VisualBlog

2009-09-21T15:29:39Z

Jvs:

__NOTOC__
<gallery caption="2009" widths="200px" perrow="4">
Image:Slicer3-mac-64bit-2009-09-11.mov|Interactive volume rendering of 512x512x1749 CT volume on 64 bit build of slicer for Mac OSX 10.6.
Image:Registration-module-hierarchy-prototype.png|Proptype hierarchy of registration modules for specific use-cases that present a simpler view of the capabilities of RegisterImages.
Image:Xoran-Cone-beam-CT_Craniofacial_Asymetry-2009-08-27.png|Example experiment in craniofacial surgery planning by mirroring one side of the skull to the other. This example was done in collaboration with Will van Kampen of [http://xorantech.com Xoran Technologies] and was a follow up to the August 25 [http://www.na-mic.org/Wiki/index.php/Events:Slicer_Workshop_August_2009 Slicer IGT Workshop] in Boston.
Image:Bioimagesuite slicer1.png|[http://www.bioimagesuite.org BioImageSuite] module being discovered.
Image:Bioimagesuite slicer2.png|[http://www.bioimagesuite.org BioImageSuite] modules in menu.
Image:Bioimagesuite slicer3.png|Autogenerated [http://www.bioimagesuite.org BioImageSuite] module GUI.
Image:Bioimagesuite slicer4.png|Slicer command line module recognized and loaded in [http://www.bioimagesuite.org BioImageSuite].
Image:BIS-Slicer-2009-08-13.jpg|Xenios Papademetris enabled the tools in [http://www.bioimagesuite.org BioImageSuite] to work as command line modules in slicer.
Image:2009JuneJulyStats.png|See [http://www.slicer.org/pages/Special:Download_Stats?order=downloads&reverse=1 here] for download statistics (page might take a while to load). The Piechart demonstrates the download proportions between the different OS.
Image:Stochastic-Tractography-01040-lh-all-3D-cropped.png|[http://www.na-mic.org/Wiki/index.php/Summer2009:VCFS '''New Stochastic Tractography'''] tools for analysis of diffusion volumes implemented as Python modules by Julien de Siebenthal.
Image:3DSlicerFourDAnalysis Screenshot.png |[http://www.na-mic.org/Wiki/index.php/2009_Summer_Project_Week_4D_Imaging '''Four Dimensional Image (Time Series) Analysis'''] Junichi Tokuda has implemented a slicer module for dynamic MR analysis and a general framework for working with time series volume groups.
Image:Slicer dti seeding or.jpg|[http://www.na-mic.org/Wiki/index.php/2009_Summer_Project_Week_Slicer3_Brainlab_Introduction '''Intraoperative navigation experiments'''] integrate slicer3 with the commercial [http://www.brainlab.com/scripts/website_english.asp BrainLab] system and Yale's [http://bioimagesuite.org/ BioImageSuite] software.
Image:SkullStrippingInSlicer.png|'''New [http://www.na-mic.org/Wiki/index.php/2009_Summer_Project_Week_Skull_Stripping skull stripping extension module]''' implemented by Xiaodong Tao.
Image:MS-TSA-CompareView.png|'''CompareView for Longitudinal Visualization of MS''' implemented by Jim Miller and demonstrated using a set of 5 scans of a patient with multiple sclerosis. Data provided by Dominik Meier of the [http://cni.bwh.harvard.edu Center for Neurological Imaging]
</gallery>
<gallery caption="2008" widths="200px" perrow="4">
Image:Synarc-Li-Level tracing.gif|'''Constrained Level Tracing Algorithm''' implemented by Andrew Li and his team at [http://synarc.com/ Synarc] built on the Slicer3 Editor module has been deployed for bone density measurements in support of clinical trials. Synarc employees participated in the [http://www.na-mic.org/Wiki/index.php/Stanford_2008_Slicer_Workshop 2008 Slicer Training] event at Stanford University.
Image:DebrecenTumorMovieStartFrame.png|'''Start frame from [[Tumor_Movie_from_Debrecen|time lapse movie]] showing "Chameleon Tumor" progression.''' Video courtesy by Ervin Berenyi and Andras Jakab, Department of Medical Laboratory and Diagnostic Imaging, University of Debrecen Medical School and Health Science Center.
Image:Femesh-in-trunk-120808.png|'''Image showing the [http://www.na-mic.org/Wiki/index.php/NA-MIC_NCBC_Collaboration:Automated_FE_Mesh_Development IA-FEMesh] module in Slicer3.''' This image shows the display of material properties assigned to a hexahedral mesh. This image was created by Curl Lisle, Nicole Grosland, Kiran Shivanna, Steve Pieper, and Vincent Magnotta
Image:VascularLesionSegmentation.jpg|'''Image showing the segmentation of vasular lesions based on T1, T2 and FLAIR images.''' A Bayesian classification is performed to label each of the voxels as grey matter, white matter, CSF, and lesion.
Image:ClipModel-with-widget.png|The new Clip Model Module (Alex Yarmarkovich) uses a VTK box widget to select cutting planes to clip a selected model.
Image:PythonDistanceTransform.png|Distance Transform from a label map calculated by Steve Pieper using the NumpyScript module created by Luca Antiga. See [[Slicer3:Python]] for more info.
Image:DTI-Visualization-Neurosurgical-Tutorial.png|Exploring DTI visualization using the [http://wiki.na-mic.org/Wiki/index.php/Slicer3.2:Training Neurosurgical Tutorial]. A virtual probe (fiducial) was positioned in the motor cortex and used as a seed for tractography. The region adjacent to the tumor was used as a seeding area for a separate tractography, which is represented as thin lines with ellipsoid glyphs.
Image:Color-image-reslice-2008-06-11.png|'''Color Image Reslice''' Demonstrates the ability to read a sequence of jpg files as a color volume and apply 3D interactive reslice tools. Image data is Visible Human 2 courtesy of the [http://nac.spl.harvard.edu/pages/Research_Cores#Clinical_Computational_Anatomy_Core NAC Clinical Computational Anatomy Core]
Image:Andras-Jakab-Debrecen-gamma01.jpg|'''Planning for CT Radiosurgery augmented with diffusion tractography (fibers: internal capsule, corpus callosum and the environment of the tumor, which is a metastatic tumor in the parietal lobe)''' Image Courtesy of University of Debrecen, Medical School and Health Science Center [[Debrecen | more information...]]
Image:Debrecen slicer 01.jpg|'''Integration of diffusion and structural imaging for tumor visualization''' Image Courtesy of University of Debrecen, Medical School and Health Science Center
Image:Slicer_IGTL_NITRobot.jpg|'''Integration of Neurosurgical Robot and Slicer using OpenIGTLink, February 2008''' Joint team of Nagoya Institute of Technology and Brigham and Women's Hospital demonstrated a prototype integration of neurosurgical robot and 3D Slicer using OpenIGTLink.
Image:Cardioseg+volume.png|'''Cardiac segmentation and CT Volume Rendering, February 2008''' Using data and segmentations from the [http://wiki.na-mic.org/Wiki/index.php/NA-MIC_Childrens_Collaboration collaboration with Boston Children's Hospital Pediatric Cardiology].
Image:Slicer_IGTL_PartialImage.png|'''Partial image update using OpenIGTLink, February 2008''' [http://wiki.na-mic.org/Wiki/index.php/OpenIGTLink OpenIGTLink] allows an external imaging scanner (Ultrasound/CT/MR) to update part of a volume, which has already been loaded on the Slicer. This is helpful if the imaging plane sweeps the subject, and images are transfered to the Slicer on-the-fly.
Image:Slicer_CudaHead.jpg|'''The First MRML node rendering using CUDA February 2008''' [[Slicer3:Volume_Rendering_With_Cuda| Cuda Volume Rendering]] provides a Volume Rendering Method on the new and advanced NVidia Hardware.
Image:Slicer_OpenIGTLINK.png|'''The First Implementation of OpenIGTLink, January 2008''' [http://wiki.na-mic.org/Wiki/index.php/OpenIGTLink OpenIGTLink] protocol provides plug-and-play connectivity to tracking devices, imagers (MR, ultrasound ...) and other medical devices. A real-time image transfer to the Slicer in 10 fps is demonstrated in the screenshot.
Image:Slicer_TrackerDaemon_IGSTK.png|'''Image from Haiying Liu, Patrick Cheng, Noby Hata, Junichi Tokuda, Luis Ibanez, and Steve Pieper, January 2008.''' In the NAMIC All Hands Meeting 2008, the bi-directional socket communication has been established between the Tracker Daemon in Slicer 3 and IGSTK server which acquires tracking data from device and sends it to Tracker Daemon. The speed of communication is controlled by Slicer.
</gallery>
<gallery caption="2007" widths="200px" perrow="4">
Image:ENT.png|'''Image from Jaesung Hong December 2007''' Visualization of cochlea(green) and facial nerve(red) for ENT navigation. We are moving on from Slicer2 to Slicer3 at Kyushu University Hospital in Japan.
Image:Slicer-igstk.png|'''Image from Steve Pieper, Luis Ibanez, Haiying Liu December 2007''' Result of [http://wiki.na-mic.org/Wiki/index.php/2007_December_Slicer_IGT_Programming Slicer for IGT workshop] showing Slicer3 transform node being updated by a [http://www.igstk.org IGSTK] tracker process.
Image:VolumeRenderScene.png|'''Image from Steve Pieper, Andy Freudling December 2007''' More volume rendering examples. New Threshold tool makes it easy to visualize surfaces.
Image:Canine-heart1.png|'''Image from Steve Pieper, December 2007''' Display of segmented heart data results using volume rendering inside Slicer3. See [https://caportal.cis.jhu.edu/ JHU Computational Anatomy Portal] for more information.
Image:Arcuatetractvolume2.png|'''Image from Tri Ngo and Steve Pieper, November 2007''' Display of Stochastic Tractography results using volume rendering inside Slicer3. See [http://wiki.na-mic.org/Wiki/index.php/Algorithm:MIT:DTI_StochasticTractography '''here'''] for more information.
Image:VolumeRenderingBoneDetection.png|'''Image from Andy Freudling on October 2007''' First results of volume rendering inside Slicer3. See [http://wiki.na-mic.org/Wiki/index.php/Slicer3:Volume_Rendering '''here'''] for more information.
Image:sirp1.png|'''Image from wjp on Wednesday, October 24, 2007''' QueryAtlas visualizing combined morphology and functional analyses generated by running FreeSurfer and a FIPS pipeline on a BIRN phaseII SIRP dataset. Interactive annotations (on mouse-over) are being translated thru Slicer's controlled vocabulary.
Image:SlicerReformat.png|'''Image from Jim on Saturday, September 15, 2007''' Slice viewers can be used to specify oblique reformats using the 'Reformat' orientation (instead of axial, coronal, sagittal) and CTRL-Right-Button-Move (subject to change).
Image:Livers.png|'''Image from Dirk, Matthew, Jim, and Steve on Monday, August 13, 2007''' A new label map smoothing tool has been added to help with our [http://wiki.na-mic.org/Wiki/index.php/NA-MIC_Collaborations#Children.27s_Pediatric_Cardiology_Collaboration_with_SCI.2FSPL.2FNortheastern collaboration with Children's Hospital Boston, SCI at University of Utah and Northeastern University]. The unfiltered labelmap is shown in blue, and the filtered results are shown in peach.
Image:Editbox.png|'''Image from Steve and Wendy on Monday, August 6, 2007''' New Editor functionality, with EditBox which is invoked using the F1 key (will soon be moved to the space bar).
Image:EMSegment31Structures.png|'''Image from Brad and Kilian on Wednesday, June, 21, 2007''' Example of [http://wiki.na-mic.org/Wiki/index.php/Projects/Structural/2007_Project_Week_EMSegmentation_Validation EMSegmenter in Slicer3]
Image:ConnectivityMap.png|'''Image from pieper on Friday, June, 9, 2007''' Slicer3 Module for [http://wiki.na-mic.org/Wiki/index.php/Algorithm:MIT:DTI_StochasticTractography Stochastic Tractography] from MIT (Ngo, Golland) and BWH (Westin, Kubicki).
Image:kwmeshvisu-slicer-logo.png|'''Image from ipek on Wednesday, June, 6, 2007''' UNC Logo in Slicer3 for KWMeshVisu (Ipek Oguz, Martin Styner).
Image:CineDisplayDesigns.png|'''Image from wjp on Wednesday, May, 30, 2007''' Design mockups for Slicer3's Cine Display interface (William Leue, Wendy Plesniak).
Image:Atlas-2007-05-16.png|'''Image from pieper on Tuesday, May, 30, 2007''' The SPL-PNL brain atlas loaded in Slicer3. Demonstrates model hierarchy and clipping.
Image:EMSegmentation_Results_Screenshot.png|'''Image from davisb on Monday, April, 27, 2007''' EMSegment screenshot---segmentation results and work-flow GUI
Image:Mimx.png|'''Image from magnotta on Monday, April, 16, 2007''' Mimx Logo in Slicer3 for VoxelMeshingModule
Image:PythonMenu.png |'''Image from blezek on Tuesday, April, 10, 2007 at 8:00AM''' Python incorporated into [[Slicer3:Python| Slicer]]. [[Slicer3:VisualBlog_Extension#Image_from_blezek_on_Tuesday.2C_April.2C_10.2C_2007_at_8:00AM | More ...]]
Image:ZoomWindow.png|'''Image from wjp on Thursday, March 22, 2007 at 10:00AM''' New GUI elements: Shows a magnified view in the GUI panel of an area around the mouse in any Slice Window.
Image:NavigationWindow.png|'''Image from wjp on Thursday, March 22, 2007 at 10:00AM''' New GUI elements: Shows birds-eye-view of the scene relative to the outline of the 3D Viewer's window in the 'Manipulate 3D View' GUI panel.
Image:Slicer3FirstTractography.png|'''Image from pieper on Tuesday, January 16, 2007 at 7:58PM''' From Lauren, shows fiber tracts loaded from a file and with display properties controlled by the GUI.
</gallery>
<gallery caption="2006" widths="200px" perrow="4">
Image:S3GUI-12-29-06.png|'''Image from wjp on Friday, December 29, 2006 at 3:23PM''' Module choose and navigation functionality integrated into the application toolbar to create more space for module GUIs on the side panel. Slice Controller widgets also updated to have more functionality available, a button to link and unlink their control, and an improved visual design.
Image:S3GUIWithLogo.png|'''Image from wjp on Monday, November 28, 2006 at 6:40M''' New 3D Slicer logo integrated with slicer GUI.
Image:QueryAtlas-fBIRN-Slicer3-2006-10-23.png|'''Image from pieper on Thursday, October 26, 2006 at 1:54M''' FreeSurfer structural data (cortical and subcortical segmentation) with fBIRN functional overlay, shown as part of Slicer3-based BIRN Query Atlas project.
Image:Clipping.png|'''Image from pieper on Thursday, October 05, 2006 at 1:08PM''' Clipping with the slice plane is now supported, along with thresholded image display.
Image:FreeSurfer-Curvature-2006-09-08.png|'''Image from naucoin on Friday, September 08, 2006 at 12:14pm''' The FreeSurfer colour lookup table has been added to the Slicer3 FreeSurfer Library. A curvature overlay file was loaded and displayed on bert/surf/lh.pial as loaded in via the Models module.
Image:FreeSurfer-Annotation-2006-09-08-B.png|'''Image from naucoin on Friday, September 08, 2006 at 11:24am''' The FreeSurfer scalar reader has been integrated as a Slicer 3 Library, and surfaces can be read via the Models module. Shot shows standard bert/surf/lh.pial plus a test script to load the annotation labels file.
Image:Editor-module-prototype.png|'''Image from pieper on Tuesday, August 08, 2006 at 4:26PM''' A number of things have come together to allow the new prototype editor module. [[Slicer3:VisualBlog_Extension#Image from pieper on Tuesday, August 08, 2006 at 4:26PM | More ...]]
Image:Oblique-slice-test.png|'''Image from pieper on Friday, July 28, 2006 at 9:04AM''' Test of making a non-orthogonal slice plane. This was created by manually setting the SliceToRAS matrix in the vtkMRMLSliceNode. GUI is not yet hooked up for oblique slices.
Image:Single-pixel.png|'''Image from pieper on Thursday, July 27, 2006 at 5:21PM''' Shows that a single pixel voxel in black is exactly bounded by a unit cube in RAS space. Also the blinking eye buttons for slice visiblility are hooked up and there is now a red-yellow-green color coding for the slice windows (carried over from slicer2).
Image:Textured-slice-planes.png|'''Image from pieper on Thursday, July 13, 2006 at 4:49PM''' Test of interactive slice textured plane control. Not yet eneabled through GUI, but driven by a [http://www.na-mic.org:8000/websvn/filedetails.php?repname=Slicer3&path=%2Ftrunk%2FBase%2FGUI%2FTesting%2FTestSliceModels.tcl&rev=0&sc=1 test script] that you can source into the console. [[Slicer3:VisualBlog_Extension#Image from pieper on Thursday, July 13, 2006 at 4:49PM | More ...]]
Image:Slicer3-lung.png|'''Image from pieper on Tuesday, July 11, 2006 at 3:39PM''' Example model read from vtk file and loaded in slicer3
Image:Logo-widget.png|'''Image from pieper on Monday, July 03, 2006 at 3:35PM''' Test of the new logo widget for adding module-specific watermark logos directly in the 3d view. Uses a vtkLogoWidget from VTK cvs head. Kitware is working on cmake support to notify developers when a VTK cvs update is needed. Once that is done, the logo code will be added to slicer3 svn.
Image:Slicer3-pan-zoom-anno-2006-06-26.png|'''Image from pieper on Monday, June 26, 2006 at 10:38AM''' New annotations and key bindings. Middle mouse to pan, right mouse to zoom.
Image:Slicer3_command-line-median-filter-2006-06-21.png|'''Image by pieper on Wednesday, June 21, 2006 at 1:01PM''' results of the command line median filter module
Image:SlicerScreenShot7.png|'''Image by millerjv on Tuesday, June 20, 2006 at 4:37PM''' {First command line module to export data, execute, and import data back into Slicer}
Image:SlicerScreenShot5.png|'''Image by millerjv on Friday, June 16, 2006 at 11:15AM''' {Command line module with an enumerated parameter as a radio button}
Image:Slicer3ApplicationSettings.png|'''Image by millerjv on Wednesday, June 14, 2006 at 10:20AM''' {Slicer applications settings panel showing the module search path}
Image:SlicerScreenShot2.png|'''Image from pieper on Tuesday, June 13, 2006 at 8:23PM''' Another command line module example from Jim
Image:SlicerScreenShot1.png|'''Image from pieper on Tuesday, June 13, 2006 at 8:20PM''' Example from Jim Miller showing the automatic GUI generation from XML collected from execution module commands
Image:Slicer-sample-2006-06-13.png|'''Image from pieper on Tuesday, June 13, 2006 at 8:18PM''' Example screen shot showing that there is a basic interface in place.
</gallery>
 

== About the VisualBlog ==

The VisualBlog is meant to be an easy place to upload screenshot so that both developers and outside observes can track the progress of the project.

Many thanks to developers and users for contributing their images here.

Modules:StochasticTractography-Documentation-3.4

2009-04-16T18:52:44Z

Jvs:

[[Documentation-3.4|Return to Slicer 3.4 Documentation]]
__NOTOC__
===Module Name===
Stochastic Tractography

{|
|[[Image:Cc_01.png|thumb|280px|Corpus callosum with stochastic tractography]]
|[[Image:Cc_stoch.png|thumb|280px|Corpus callosum lateral projections]]
|}

== General Information ==
===Module Type & Category===

Type: Interactive

Category: DTI

===Authors, Collaborators & Contact===
* Author: Julien von Siebenthal
* Contributor: Steve Pieper
* Contact: jvs@bwh.harvard.edu

===Module Description===
As a main purpose, the stochastic tractography module helps to evaluate connectivity between two regions of interest (ROIs) of the brain. These ROIs define generally grey matter regions having a specific neurophysiological function. Extensively, study involving more than two regions could still be done by pairing the regions two by two.

To go deeper into learning the module you can download the following [http://www.na-mic.org/Wiki/index.php/Python_Stochastic_Tractography_Tutorial tutorial]

== Usage ==
* You want to study fiber path from a single region of interest (ROI)
* You want to evaluate connectivity between two ROIs

=== Description ===

{|
|[[Image:General.png|thumb|1000px|Stochastic tractography panel]]
|}

With the stochastic tractography module, you can:
{|
|
* Feature 1 : smooth the given Diffusion Weighted Image (DWI) using a Half Width Full Maximum gaussian filter
{|
|[[Image:smooth2.png|thumb|500px|Smoothing step]]
|}
|}

{|
|
* Feature 2 : generate a brain mask from the DWI baseline input
{|
|[[Image:mask2.png|thumb|500px|Brain mask step]]
|}
|}

{|
|
* Feature 3 : create a DTI (Diffusion Tensor Image) tensor from the DWI input
{|
|[[Image:tensor2.png|thumb|500px|Tensor step]]
|}
|}

{|
|
* Feature 4 : produce different measures based on the tensor like fractional anistropy (FA), mode and trace
{|
|[[Image:fa2.png|thumb|500px|Tensor step: FA]]
|[[Image:mode2.png|thumb|500px|Tensor step: mode]]
|[[Image:trace2.png|thumb|500px|Tensor step: trace]]
|}
|}

{|
|
* Feature 5 : produce connection maps in case 2 ROIs are given without ROI filtering from the tractography
** showing union and intersection of both maps from region A to region B and B to A
{|
|[[Image:AorB2.png|thumb|500px|Union of A to B and B to A]]
|[[Image:AandB2.png|thumb|500px|Intersection of A to B and B to A]]
|}
|}

{|
|
* Feature 6 : produce connection maps in case 2 ROIs are given with ROI filtering from the tractography
** showing only tracts connecting region A to region B and B to A
{|
|[[Image:connectAB2.png|thumb|500px|ROI filtering]]
|[[Image:A2B2.png|thumb|500px|ROI filtering from A to B]]
|[[Image:B2A2.png|thumb|500px|ROI filtering from B to A]]
|}
|}

===Quick Tour of Features and Use===

{|
|
* '''IO panel:'''
** Input DWI Volume: the DWI is loaded through the Volume module - it is th only mandatory input
** Input ROI Volume (A/B): only 1 ROI is needed to achieve a tractography. If you want to evaluate the connection between two regions, you will give both ROIs
** Input WM Volume: a white matter mask can be given as input to use ones provided by other tools or Slicer modules - it will supersede the brain mask even if enabled. Be mindful in setting a WM: tractography results can be impaired by a too restrictive WM
** You are not obliged to set the ROIs or the white matter mask to smooth the DWI, create the brain mask and the tensor. These 3 features just require a DWI
{|
|[[Image:IOmenu.png|thumb|500px|IO step]]
|}
|}

{|
|
* '''Smoothing panel:'''
** Gaussian FWHM: this filter defines a Full Width Half Maximum. You can define it for each direction in modifying each component of the 3-vector
** Advice: you can enable solely that functionality and compute several times with different parameters till satisfaction
{|
|[[Image:Smoothmenu.png|thumb|500px|Smoothing step]]
|}
|}

{|
|
* '''Brain Mask panel:'''
** Lower/Higher Brain Threshold: this filter is based on a simple level set segmentation - intensities of the baseline lying between the two values will be represented, others are set to 0. The most common use of this filter is to remove ventricles from the tractography domain and most of the outside of the brain
** Advice: you can enable solely that functionality and compute several times with different parameters till satisfaction
{|
|[[Image:Maskmenu.png|thumb|500px|Brain mask step]]
|}
|}

{|
|
* '''Diffusion Tensor panel:'''
** Important: this step is not mandatory. It is here to evaluate the whole tensor and achieve measurements like FA, mode or trace. You did not need it to achieve tractography
** FA, mode and trace are sent as scalar volumes and inserted in the MRML tree to be further used
** Advice: you can enable solely that functionality and compute several times with different parameters till satisfaction
{|
|[[Image:Tensormenu.png|thumb|500px|Tensor step]]
|}
|}

{|
|
* '''Tractography panel:''' This panel deals with the tractography per se:
** Total tracts: number of generated tracts per voxel
** Maximum tract length (mm): set the maximum length a tract could reach
** Step size (mm): is the step length for the update vector
** Use spacing: must be used with caution - activate spacing of the update vector
** Stopping criteria: FA is used as the stopping criteria. Advice: as ROIs are defined in the grey matter FA are generally very low, therefore do not use it in most cases
{|
|[[Image:Tractomenu.png|thumb|500px|Tractography step]]
|}
|}

{|
|
* '''Connectivity Map panel:''' This panel lets the user modify parameters to create density/connectivity maps. A map is a scalar volume storing the number of times each voxel is traversed by tracts. It can be counted differently which is the purpose of the following parameters:
** Computation mode:
*** binary: voxel counter is incremented by 1 only once
*** cumulative: voxel counter is incremented by 1 each time a tract traverses it
*** weighted: same as cumulative but the increment is the length of the tract traversing the voxel
** Length based: must be enabled if the resulting tracts must be subdivided related to their length ownership
*** dThird: tracts only counted have length between 1 and (maximum tract length)/3
*** mThird: tracts only counted have length between (maximum tract length)/3 and 2 * (maximum tract length)/3
*** uThird: tracts only counted have length between 2 * (maximum tract length)/3 and (maximum tract length)
*** vicinity: in case of 2 ROIs connectivity assessment, setting vicinity to a positive value creates a neighborhood (in voxels) around the ROIs. This could help in counting tracts that ternminate near the ROIs but not accurately in
*** threshold: defines the connection probability under which tracts are rejected
{|
|[[Image:Connectmenu.png|thumb|500px|Connectivity step]]
|}
|}

== Development ==

===Dependencies===

Volumes

===Known bugs===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker.

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

== More Information ==

===Acknowledgment===
National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149 (to Ron Kikinis, Marek Kubicki).

===References===
* [http://lmi.bwh.harvard.edu/papers/pdfs/2002/bjornemoMICCAI02.pdf Björnemo M, Brun A, Kikinis R, Westin CF. Regularized stochastic white matter tractography using diffusion tensor MRI. In Fifth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI'02). Tokyo, Japan, 2002;435-442.]
* [http://lmi.bwh.harvard.edu/papers/pdfs/2006/frimanTMI06.pdf Friman, O., Farneback, G., Westin CF. A Bayesian Approach for Stochastic White Matter Tractography. IEEE Transactions on Medical Imaging, Vol 25, No. 8, Aug. 2006]
* [http://www.na-mic.org/Wiki/index.php/Image:IC_posternew.png Shenton, M.E., Ngo, T., Rosenberger, G., Westin, C.F., Levitt, J.J., McCarley, R.W., Kubicki, M. Study of Thalamo-Cortical White Matter Fiber Tract Projections in Schizophrenia Using Diffusion Stochastic Tractography. Poster presented at the 46th Meeting of the American College of Neuropsychopharmacology, Boca Raton, FL, December 2007.]

Modules:StochasticTractography-Documentation-3.4

2009-04-16T18:50:00Z

Jvs:

[[Documentation-3.4|Return to Slicer 3.4 Documentation]]
__NOTOC__
===Module Name===
Stochastic Tractography

{|
|[[Image:Cc_01.png|thumb|280px|Corpus callosum with stochastic tractography]]
|[[Image:Cc_stoch.png|thumb|280px|Corpus callosum lateral projections]]
|}

== General Information ==
===Module Type & Category===

Type: Interactive

Category: DTI

===Authors, Collaborators & Contact===
* Author: Julien von Siebenthal
* Contributor: Steve Pieper
* Contact: jvs@bwh.harvard.edu

===Module Description===
As a main purpose, the stochastic tractography module helps to evaluate connectivity between two regions of interest (ROIs) of the brain. These ROIs define generally grey matter regions having a specific neurophysiological function. Extensively, study involving more than two regions could still be done by pairing the regions two by two.

To go deeper into learning the module you can download the following [http://www.na-mic.org/Wiki/index.php/Python_Stochastic_Tractography_Tutorial tutorial]

== Usage ==
* You want to study fiber path from a single region of interest (ROI)
* You want to evaluate connectivity between two ROIs

=== Description ===

{|
|[[Image:General.png|thumb|1000px|Stochastic tractography panel]]
|}

With the stochastic tractography module, you can:
{|
|
* Feature 1 : smooth the given Diffusion Weighted Image (DWI) using a Half Width Full Maximum gaussian filter
{|
|[[Image:smooth2.png|thumb|500px|Smoothing step]]
|}
|}

{|
|
* Feature 2 : generate a brain mask from the DWI baseline input
{|
|[[Image:mask2.png|thumb|500px|Brain mask step]]
|}
|}

{|
|
* Feature 3 : create a DTI (Diffusion Tensor Image) tensor from the DWI input
{|
|[[Image:tensor2.png|thumb|500px|Tensor step]]
|}
|}

{|
|
* Feature 4 : produce different measures based on the tensor like fractional anistropy (FA), mode and trace
{|
|[[Image:fa2.png|thumb|500px|Tensor step: FA]]
|[[Image:mode2.png|thumb|500px|Tensor step: mode]]
|[[Image:trace2.png|thumb|500px|Tensor step: trace]]
|}
|}

{|
|
* Feature 5 : produce connection maps in case 2 ROIs are given without ROI filtering from the tractography
** showing union and intersection of both maps from region A to region B and B to A
{|
|[[Image:AorB2.png|thumb|500px|Union of A to B and B to A]]
|[[Image:AandB2.png|thumb|500px|Intersection of A to B and B to A]]
|}
|}

{|
|
* Feature 6 : produce connection maps in case 2 ROIs are given with ROI filtering from the tractography
** showing only tracts connecting region A to region B and B to A
{|
|[[Image:connectAB2.png|thumb|500px|ROI filtering]]
|[[Image:A2B2.png|thumb|500px|ROI filtering from A to B]]
|[[Image:B2A2.png|thumb|500px|ROI filtering from B to A]]
|}
|}

===Quick Tour of Features and Use===

{|
|
* '''IO panel:'''
** Input DWI Volume: the DWI is loaded through the Volume module - it is th only mandatory input
** Input ROI Volume (A/B): only 1 ROI is needed to achieve a tractography. If you want to evaluate the connection between two regions, you will give both ROIs
** Input WM Volume: a white matter mask can be given as input to use ones provided by other tools or Slicer modules - it will supersede the brain mask even if enabled. Be mindful in setting a WM: tractography results can be impaired by a too restrictive WM
** You are not obliged to set the ROIs or the white matter mask to smooth the DWI, create the brain mask and the tensor. These 3 steps just require a DWI
{|
|[[Image:IOmenu.png|thumb|500px|IO step]]
|}
|}

{|
|
* '''Smoothing panel:'''
** Gaussian FWHM: this filter defines a Full Width Half Maximum. You can define it for each direction in modifying each component of the 3-vector
** Advice: you can enable solely that functionality and compute several times with different parameters till satisfaction
{|
|[[Image:Smoothmenu.png|thumb|500px|Smoothing step]]
|}
|}

{|
|
* '''Brain Mask panel:'''
** Lower/Higher Brain Threshold: this filter is based on a simple level set segmentation - intensities of the baseline lying between the two values will be represented, others are set to 0. The most common use of this filter is to remove ventricles from the tractography domain and most of the outside of the brain
** Advice: you can enable solely that functionality and compute several times with different parameters till satisfaction
{|
|[[Image:Maskmenu.png|thumb|500px|Brain mask step]]
|}
|}

{|
|
* '''Diffusion Tensor panel:'''
** Important: this step is not mandatory. It is here to evaluate the whole tensor and achieve measurements like FA, mode or trace. You did not need it to achieve tractography
** FA, mode and trace are sent as scalar volumes and inserted in the MRML tree to be further used
** Advice: you can enable solely that functionality and compute several times with different parameters till satisfaction
{|
|[[Image:Tensormenu.png|thumb|500px|Tensor step]]
|}
|}

{|
|
* '''Tractography panel:''' This panel deals with the tractography per se:
** Total tracts: number of generated tracts per voxel
** Maximum tract length (mm): set the maximum length a tract could reach
** Step size (mm): is the step length for the update vector
** Use spacing: must be used with caution - activate spacing of the update vector
** Stopping criteria: FA is used as the stopping criteria. Advice: as ROIs are defined in the grey matter FA are generally very low, therefore do not use it in most cases
{|
|[[Image:Tractomenu.png|thumb|500px|Tractography step]]
|}
|}

{|
|
* '''Connectivity Map panel:''' This panel lets the user modify parameters to create density/connectivity maps. A map is a scalar volume storing the number of times each voxel is traversed by tracts. It can be counted differently which is the purpose of the following parameters:
** Computation mode:
*** binary: voxel counter is incremented by 1 only once
*** cumulative: voxel counter is incremented by 1 each time a tract traverses it
*** weighted: same as cumulative but the increment is the length of the tract traversing the voxel
** Length based: must be enabled if the resulting tracts must be subdivided related to their length ownership
*** dThird: tracts only counted have length between 1 and (maximum tract length)/3
*** mThird: tracts only counted have length between (maximum tract length)/3 and 2 * (maximum tract length)/3
*** uThird: tracts only counted have length between 2 * (maximum tract length)/3 and (maximum tract length)
*** vicinity: in case of 2 ROIs connectivity assessment, setting vicinity to a positive value creates a neighborhood (in voxels) around the ROIs. This could help in counting tracts that ternminate near the ROIs but not accurately in
*** threshold: defines the connection probability under which tracts are rejected
{|
|[[Image:Connectmenu.png|thumb|500px|Connectivity step]]
|}
|}

== Development ==

===Dependencies===

Volumes

===Known bugs===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker.

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

== More Information ==

===Acknowledgment===
National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149 (to Ron Kikinis, Marek Kubicki).

===References===
* [http://lmi.bwh.harvard.edu/papers/pdfs/2002/bjornemoMICCAI02.pdf Björnemo M, Brun A, Kikinis R, Westin CF. Regularized stochastic white matter tractography using diffusion tensor MRI. In Fifth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI'02). Tokyo, Japan, 2002;435-442.]
* [http://lmi.bwh.harvard.edu/papers/pdfs/2006/frimanTMI06.pdf Friman, O., Farneback, G., Westin CF. A Bayesian Approach for Stochastic White Matter Tractography. IEEE Transactions on Medical Imaging, Vol 25, No. 8, Aug. 2006]
* [http://www.na-mic.org/Wiki/index.php/Image:IC_posternew.png Shenton, M.E., Ngo, T., Rosenberger, G., Westin, C.F., Levitt, J.J., McCarley, R.W., Kubicki, M. Study of Thalamo-Cortical White Matter Fiber Tract Projections in Schizophrenia Using Diffusion Stochastic Tractography. Poster presented at the 46th Meeting of the American College of Neuropsychopharmacology, Boca Raton, FL, December 2007.]

Modules:StochasticTractography-Documentation-3.4

2009-04-16T16:20:17Z

Jvs:

[[Documentation-3.4|Return to Slicer 3.4 Documentation]]
__NOTOC__
===Module Name===
Stochastic Tractography

{|
|[[Image:Cc_01.png|thumb|280px|Corpus callosum with stochastic tractography]]
|[[Image:Cc_stoch.png|thumb|280px|Corpus callosum lateral projections]]
|}

== General Information ==
===Module Type & Category===

Type: Interactive

Category: DTI

===Authors, Collaborators & Contact===
* Author: Julien von Siebenthal
* Contributor: Steve Pieper
* Contact: jvs@bwh.harvard.edu

===Module Description===
As a main purpose, the stochastic tractography module helps to evaluate connectivity between two regions of interest (ROIs) of the brain. These ROIs define generally grey matter regions having a specific neurophysiological function. Extensively, study involving more than two regions could still be done by pairing the regions two by two.

== Usage ==
* You want to study fiber path from a single region of interest (ROI)
* You want to evaluate connectivity between two ROIs

=== Description ===

{|
|[[Image:General.png|thumb|1000px|Stochastic tractography panel]]
|}

With the stochastic tractography module, you can:
{|
|
* Feature 1 : smooth the given Diffusion Weighted Image (DWI) using a Half Width Full Maximum gaussian filter
{|
|[[Image:smooth2.png|thumb|500px|Smoothing step]]
|}
|}

{|
|
* Feature 2 : generate a brain mask from the DWI baseline input
{|
|[[Image:mask2.png|thumb|500px|Brain mask step]]
|}
|}

{|
|
* Feature 3 : create a DTI (Diffusion Tensor Image) tensor from the DWI input
{|
|[[Image:tensor2.png|thumb|500px|Tensor step]]
|}
|}

{|
|
* Feature 4 : produce different measures based on the tensor like fractional anistropy (FA), mode and trace
{|
|[[Image:fa2.png|thumb|500px|Tensor step: FA]]
|[[Image:mode2.png|thumb|500px|Tensor step: mode]]
|[[Image:trace2.png|thumb|500px|Tensor step: trace]]
|}
|}

{|
|
* Feature 5 : produce connection maps in case 2 ROIs are given without ROI filtering from the tractography
** showing union and intersection of both maps from region A to region B and B to A
{|
|[[Image:AorB2.png|thumb|500px|Union of A to B and B to A]]
|[[Image:AandB2.png|thumb|500px|Intersection of A to B and B to A]]
|}
|}

{|
|
* Feature 6 : produce connection maps in case 2 ROIs are given with ROI filtering from the tractography
** showing only tracts connecting region A to region B and B to A
{|
|[[Image:connectAB2.png|thumb|500px|ROI filtering]]
|[[Image:A2B2.png|thumb|500px|ROI filtering from A to B]]
|[[Image:B2A2.png|thumb|500px|ROI filtering from B to A]]
|}
|}

* [http://www.na-mic.org/Wiki/index.php/Python_Stochastic_Tractography_Tutorial link tutorial]
===Quick Tour of Features and Use===

{|
|
* '''IO panel:'''
** Input DWI Volume: the DWI is loaded through the Volume module - it is th only mandatory input
** Input ROI Volume (A/B): only 1 ROI is needed to achieve a tractography. If you want to evaluate the connection between two regions, you will give both ROIs
** Input WM Volume: a white matter mask can be given as input to use ones provided by other tools or Slicer modules - it will supersede the brain mask even if enabled. Be mindful in setting a WM: tractography results can be impaired by a too restrictive WM
** You are not obliged to set the ROIs or the white matter mask to smooth the DWI, create the brain mask and the tensor. These 3 steps just require a DWI
{|
|[[Image:IOmenu.png|thumb|500px|IO step]]
|}
|}

{|
|
* '''Smoothing panel:'''
** Gaussian FWHM: this filter defines a Full Width Half Maximum. You can define it for each direction in modifying each component of the 3-vector
** Advice: you can enable solely that functionality and compute several times with different parameters till satisfaction
{|
|[[Image:Smoothmenu.png|thumb|500px|Smoothing step]]
|}
|}

{|
|
* '''Brain Mask panel:'''
** Lower/Higher Brain Threshold: this filter is based on a simple level set segmentation - intensities of the baseline lying between the two values will be represented, others are set to 0. The most common use of this filter is to remove ventricles from the tractography domain and most of the outside of the brain
** Advice: you can enable solely that functionality and compute several times with different parameters till satisfaction
{|
|[[Image:Maskmenu.png|thumb|500px|Brain mask step]]
|}
|}

{|
|
* '''Diffusion Tensor panel:'''
** Important: this step is not mandatory. It is here to evaluate the whole tensor and achieve measurements like FA, mode or trace. You did not need it to achieve tractography
** FA, mode and trace are sent as scalar volumes and inserted in the MRML tree to be further used
** Advice: you can enable solely that functionality and compute several times with different parameters till satisfaction
{|
|[[Image:Tensormenu.png|thumb|500px|Tensor step]]
|}
|}

{|
|
* '''Tractography panel:''' This panel deals with the tractography per se:
** Total tracts: number of generated tracts per voxel
** Maximum tract length (mm): set the maximum length a tract could reach
** Step size (mm): is the step length for the update vector
** Use spacing: must be used with caution - activate spacing of the update vector
** Stopping criteria: FA is used as the stopping criteria. Advice: as ROIs are defined in the grey matter FA are generally very low, therefore do not use it in most cases
{|
|[[Image:Tractomenu.png|thumb|500px|Tractography step]]
|}
|}

{|
|
* '''Connectivity Map panel:''' This panel lets the user modify parameters to create density/connectivity maps. A map is a scalar volume storing the number of times each voxel is traversed by tracts. It can be counted differently which is the purpose of the following parameters:
** Computation mode:
*** binary: voxel counter is incremented by 1 only once
*** cumulative: voxel counter is incremented by 1 each time a tract traverses it
*** weighted: same as cumulative but the increment is the length of the tract traversing the voxel
** Length based: must be enabled if the resulting tracts must be subdivided related to their length ownership
*** dThird: tracts only counted have length between 1 and (maximum tract length)/3
*** mThird: tracts only counted have length between (maximum tract length)/3 and 2 * (maximum tract length)/3
*** uThird: tracts only counted have length between 2 * (maximum tract length)/3 and (maximum tract length)
*** vicinity: in case of 2 ROIs connectivity assessment, setting vicinity to a positive value creates a neighborhood (in voxels) around the ROIs. This could help in counting tracts that ternminate near the ROIs but not accurately in
*** threshold: defines the connection probability under which tracts are rejected
{|
|[[Image:Connectmenu.png|thumb|500px|Connectivity step]]
|}
|}

== Development ==

===Dependencies===

Volumes

===Known bugs===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker.

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

== More Information ==

===Acknowledgment===
National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149 (to Ron Kikinis, Marek Kubicki).

===References===
* [http://lmi.bwh.harvard.edu/papers/pdfs/2002/bjornemoMICCAI02.pdf Björnemo M, Brun A, Kikinis R, Westin CF. Regularized stochastic white matter tractography using diffusion tensor MRI. In Fifth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI'02). Tokyo, Japan, 2002;435-442.]
* [http://lmi.bwh.harvard.edu/papers/pdfs/2006/frimanTMI06.pdf Friman, O., Farneback, G., Westin CF. A Bayesian Approach for Stochastic White Matter Tractography. IEEE Transactions on Medical Imaging, Vol 25, No. 8, Aug. 2006]
* [http://www.na-mic.org/Wiki/index.php/Image:IC_posternew.png Shenton, M.E., Ngo, T., Rosenberger, G., Westin, C.F., Levitt, J.J., McCarley, R.W., Kubicki, M. Study of Thalamo-Cortical White Matter Fiber Tract Projections in Schizophrenia Using Diffusion Stochastic Tractography. Poster presented at the 46th Meeting of the American College of Neuropsychopharmacology, Boca Raton, FL, December 2007.]

Modules:StochasticTractography-Documentation-3.4

2009-04-16T01:18:28Z

Jvs:

[[Documentation-3.4|Return to Slicer 3.4 Documentation]]
__NOTOC__
===Module Name===
Stochastic Tractography

{|
|[[Image:Cc_01.png|thumb|280px|Corpus callosum with stochastic tractography]]
|[[Image:Cc_stoch.png|thumb|280px|Corpus callosum lateral projections]]
|}

== General Information ==
===Module Type & Category===

Type: Interactive

Category: DTI

===Authors, Collaborators & Contact===
* Author: Julien von Siebenthal
* Contributor: Steve Pieper
* Contact: jvs@bwh.harvard.edu

===Module Description===
As a main purpose, the stochastic tractography module helps to evaluate connectivity between two regions of interest (ROIs) of the brain. These ROIs define generally grey matter regions having a specific neurophysiological function. Extensively, study involving more than two regions could still be done by pairing the regions two by two.

== Usage ==
* You want to study fiber path from a single region of interest (ROI)
* You want to evaluate connectivity between two ROIs

=== Description ===

{|
|[[Image:General.png|thumb|1000px|Stochastic tractography panel]]
|}

With the stochastic tractography module, you can:
{|
|
* Feature 1 : smooth the given Diffusion Weighted Image (DWI) using a Half Width Full Maximum gaussian filter
{|
|[[Image:smooth2.png|thumb|500px|Smoothing step]]
|}
|}

{|
|
* Feature 2 : generate a brain mask from the DWI baseline input
{|
|[[Image:mask2.png|thumb|500px|Brain mask step]]
|}
|}

{|
|
* Feature 3 : create a DTI (Diffusion Tensor Image) tensor from the DWI input
{|
|[[Image:tensor2.png|thumb|500px|Tensor step]]
|}
|}

{|
|
* Feature 4 : produce different measures based on the tensor like fractional anistropy (FA), mode and trace
{|
|[[Image:fa2.png|thumb|500px|Tensor step: FA]]
|[[Image:mode2.png|thumb|500px|Tensor step: mode]]
|[[Image:trace2.png|thumb|500px|Tensor step: trace]]
|}
|}

{|
|
* Feature 5 : produce connection maps in case 2 ROIs are given without ROI filtering from the tractography
** showing union and intersection of both maps from region A to region B and B to A
{|
|[[Image:AorB2.png|thumb|500px|Union of A to B and B to A]]
|[[Image:AandB2.png|thumb|500px|Intersection of A to B and B to A]]
|}
|}

{|
|
* Feature 6 : produce connection maps in case 2 ROIs are given with ROI filtering from the tractography
** showing only tracts connecting region A to region B and B to A
{|
|[[Image:connectAB2.png|thumb|500px|ROI filtering]]
|[[Image:A2B2.png|thumb|500px|ROI filtering from A to B]]
|[[Image:B2A2.png|thumb|500px|ROI filtering from B to A]]
|}
|}

* [http://www.na-mic.org/Wiki/index.php/Python_Stochastic_Tractography_Tutorial link tutorial]
===Quick Tour of Features and Use===

{|
|
* '''IO panel:'''
** Input DWI Volume: the DWI is loaded through the Volume module - it is th only mandatory input
** Input ROI Volume (A/B): only 1 ROI is needed to achieve a tractography. If you want to evaluate the connection between two regions, you will give both ROIs
** Input WM Volume: a white matter mask can be given as input to use ones provided by other tools or Slicer modules - it will supersede the brain mask even if enabled. Be mindful in setting a WM: tractography results can be impaired by a too restrictive WM
** You are not obliged to set the ROIs or the white matter mask to smooth the DWI, create the brain mask and the tensor. These 3 steps just require a DWI
{|
|[[Image:IOmenu.png|thumb|500px|IO step]]
|}
|}

{|
|
* '''Smoothing panel:'''
** Gaussian FWHM: this filter defines a Full Width Half Maximum. You can define it for each direction in modifying each component of the 3-vector
** Advice: you can enable solely that functionality and compute several times with different parameters till satisfaction
{|
|[[Image:Smoothmenu.png|thumb|500px|Smoothing step]]
|}
|}

{|
|
* '''Brain Mask panel:'''
** Lower/Higher Brain Threshold: this filter is based on a simple level set segmentation - intensities of the baseline lying between the two values will be represented, others are set to 0. The most common use of this filter is to remove ventricles from the tractography domain and most of the outside of the brain
** Advice: you can enable solely that functionality and compute several times with different parameters till satisfaction
{|
|[[Image:Maskmenu.png|thumb|500px|Brain mask step]]
|}
|}

{|
|
* '''Diffusion Tensor panel:'''
** Important: this step is not mandatory. It is here to evaluate the whole tensor and achieve measurements like FA, mode or trace. You did not need it to achieve tractography
** FA, mode and trace are sent as scalar volumes and inserted in the MRML tree to be further used
** Advice: you can enable solely that functionality and compute several times with different parameters till satisfaction
{|
|[[Image:Tensormenu.png|thumb|500px|Tensor step]]
|}
|}

{|
|
* '''Tractography panel:''' This panel deals with the tractography per se:
** Total tracts: number of generated tracts per voxel
** Maximum tract length (mm): set the maximum length a tract could reach
** Step size (mm): is the step length for the update vector
** Use spacing: must be used with caution - activate spacing of the update vector
** Stopping criteria: FA is used as the stopping criteria. Advice: as ROIs are defined in the grey matter FA are generally very low, therefore do not use it in most cases
{|
|[[Image:Tractomenu.png|thumb|500px|Tractography step]]
|}
|}

{|
|
* '''Connectivity Map panel:''' This panel lets the user modify parameters to create density/connectivity maps. A map is a scalar volume storing the number of times each voxel is traversed by tracts. It can be counted differently which is the purpose of the following parameters:
** Computation mode:
*** binary: voxel counter is incremented by 1 only once
*** cumulative: voxel counter is incremented by 1 each time a tract traverses it
*** weighted: same as cumulative but the increment is the length of the tract traversing the voxel
** Length based: must be enabled if the resulting tracts must be subdivided related to their length ownership
*** dThird: tracts only counted have length between 1 and (maximum tract length)/3
*** mThird: tracts only counted have length between (maximum tract length)/3 and 2 * (maximum tract length)/3
*** uThird: tracts only counted have length between 2 * (maximum tract length)/3 and (maximum tract length)
{|
|[[Image:Connectmenu.png|thumb|500px|Connectivity step]]
|}
|}

== Development ==

===Dependencies===

Volumes

===Known bugs===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker.

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

== More Information ==

===Acknowledgment===
National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149 (to Ron Kikinis, Marek Kubicki).

===References===
* [http://lmi.bwh.harvard.edu/papers/pdfs/2002/bjornemoMICCAI02.pdf Björnemo M, Brun A, Kikinis R, Westin CF. Regularized stochastic white matter tractography using diffusion tensor MRI. In Fifth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI'02). Tokyo, Japan, 2002;435-442.]
* [http://lmi.bwh.harvard.edu/papers/pdfs/2006/frimanTMI06.pdf Friman, O., Farneback, G., Westin CF. A Bayesian Approach for Stochastic White Matter Tractography. IEEE Transactions on Medical Imaging, Vol 25, No. 8, Aug. 2006]
* [http://www.na-mic.org/Wiki/index.php/Image:IC_posternew.png Shenton, M.E., Ngo, T., Rosenberger, G., Westin, C.F., Levitt, J.J., McCarley, R.W., Kubicki, M. Study of Thalamo-Cortical White Matter Fiber Tract Projections in Schizophrenia Using Diffusion Stochastic Tractography. Poster presented at the 46th Meeting of the American College of Neuropsychopharmacology, Boca Raton, FL, December 2007.]

Modules:StochasticTractography-Documentation-3.4

2009-04-16T01:15:33Z

Jvs:

[[Documentation-3.4|Return to Slicer 3.4 Documentation]]
__NOTOC__
===Module Name===
Stochastic Tractography

{|
|[[Image:Cc_01.png|thumb|280px|Corpus callosum with stochastic tractography]]
|[[Image:Cc_stoch.png|thumb|280px|Corpus callosum lateral projections]]
|}

== General Information ==
===Module Type & Category===

Type: Interactive

Category: DTI

===Authors, Collaborators & Contact===
* Author: Julien von Siebenthal
* Contributor: Steve Pieper
* Contact: jvs@bwh.harvard.edu

===Module Description===
As a main purpose, the stochastic tractography module helps to evaluate connectivity between two regions of interest (ROIs) of the brain. These ROIs define generally grey matter regions having a specific neurophysiological function. Extensively, study involving more than two regions could still be done by pairing the regions two by two.

== Usage ==
* You want to study fiber path from a single region of interest (ROI)
* You want to evaluate connectivity between two ROIs

=== Description ===

{|
|[[Image:General.png|thumb|1000px|Stochastic tractography panel]]
|}

With the stochastic tractography module, you can:
{|
|
* Feature 1 : smooth the given Diffusion Weighted Image (DWI) using a Half Width Full Maximum gaussian filter
{|
|[[Image:smooth2.png|thumb|500px|Smoothing step]]
|}
|}

{|
|
* Feature 2 : generate a brain mask from the DWI baseline input
{|
|[[Image:mask2.png|thumb|500px|Brain mask step]]
|}
|}

{|
|
* Feature 3 : create a DTI (Diffusion Tensor Image) tensor from the DWI input
{|
|[[Image:tensor2.png|thumb|500px|Tensor step]]
|}
|}

{|
|
* Feature 4 : produce different measures based on the tensor like fractional anistropy (FA), mode and trace
{|
|[[Image:fa2.png|thumb|500px|Tensor step: FA]]
|[[Image:mode2.png|thumb|500px|Tensor step: mode]]
|[[Image:trace2.png|thumb|500px|Tensor step: trace]]
|}
|}

{|
|
* Feature 5 : produce connection maps in case 2 ROIs are given without ROI filtering from the tractography
** showing union and intersection of both maps from region A to region B and B to A
{|
|[[Image:AorB2.png|thumb|500px|Union of A to B and B to A]]
|[[Image:AandB2.png|thumb|500px|Intersection of A to B and B to A]]
|}
|}

{|
|
* Feature 6 : produce connection maps in case 2 ROIs are given with ROI filtering from the tractography
** showing only tracts connecting region A to region B and B to A
{|
|[[Image:connectAB2.png|thumb|500px|ROI filtering]]
|[[Image:A2B2.png|thumb|500px|ROI filtering from A to B]]
|[[Image:B2A2.png|thumb|500px|ROI filtering from B to A]]
|}
|}

* [http://www.na-mic.org/Wiki/index.php/Python_Stochastic_Tractography_Tutorial link tutorial]
===Quick Tour of Features and Use===

{|
|
* '''IO panel:'''
** Input DWI Volume: the DWI is loaded through the Volume module - it is th only mandatory input.
** Input ROI Volume (A/B): only 1 ROI is needed to achieve a tractography. If you want to evaluate the connection between two regions, you will give both ROIs.
** Input WM Volume: a white matter mask can be given as input to use ones provided by other tools or Slicer modules - it will supersede the brain mask even if enabled. Be mindful in setting a WM: tractography results can be impaired by a too restrictive WM.
** You are not obliged to set the ROIs or the white matter mask to smooth the DWI, create the brain mask and the tensor. These 3 steps just require a DWI.
{|
|[[Image:IOmenu.png|thumb|500px|IO step]]
|}
|}

{|
|
* '''Smoothing panel:'''
** Gaussian FWHM: this filter defines a Full Width Half Maximum. You can define it for each direction in modifying each component of the 3-vector.
** Advice: you can enable solely that functionality and compute several times with different parameters till satisfaction.
{|
|[[Image:Smoothmenu.png|thumb|500px|Smoothing step]]
|}
|}

{|
|
* '''Brain Mask panel:'''
** Lower/Higher Brain Threshold: this filter is based on a simple level set segmentation - intensities of the baseline lying between the two values will be represented, others are set to 0. The most common use of this filter is to remove ventricles from the tractography domain and most of the outside of the brain.
** Advice: you can enable solely that functionality and compute several times with different parameters till satisfaction.
{|
|[[Image:Maskmenu.png|thumb|500px|Brain mask step]]
|}
|}

{|
|
* '''Diffusion Tensor panel:'''
** Important: this step is not mandatory. It is here to evaluate the whole tensor and achieve measurements like FA, mode or trace. You did not need it to achieve tractography.
** FA, mode and trace are sent as scalar volumes and inserted in the MRML tree to be further used.
** Advice: you can enable solely that functionality and compute several times with different parameters till satisfaction.
{|
|[[Image:Tensormenu.png|thumb|500px|Tensor step]]
|}
|}

{|
|
* '''Tractography panel:''' This panel deals with the tractography per se:
** Total tracts: number of generated tracts per voxel.
** Maximum tract length (mm): set the maximum length a tract could reach.
** Step size (mm): is the step length for the update vector.
** Use spacing: must be used with caution - activate spacing of the update vector.
** Stopping criteria: FA is used as the stopping criteria. Advice: as ROIs are defined in the grey matter FA are generally very low, therefore do not use it in most cases.
{|
|[[Image:Tractomenu.png|thumb|500px|Tractography step]]
|}
|}

{|
|
* '''Connectivity Map panel:''' This panel lets the user modify parameters to create density/connectivity maps. A map is a scalar volume storing the number of times each voxel is traversed by tracts. It can be counted differently which is the purpose of the following parameters:
** Computation mode:
*** binary: voxel counter is incremented by 1 only once
*** cumulative: voxel counter is incremented by 1 each time a tract traverses it
*** weighted: same as cumulative but the increment is the length of the tract traversing the voxel
** Length based: must be enabled if the resulting tracts must be subdivided related to their length ownership
*** dThird: tracts only counted have length between 1 and (maximum tract length)/3
*** mThird: tracts only counted have length between (maximum tract length)/3 and 2 * (maximum tract length)/3
*** uThird: tracts only counted have length between 2 * (maximum tract length)/3 and (maximum tract length)
{|
|[[Image:Connectmenu.png|thumb|500px|Connectivity step]]
|}
|}

== Development ==

===Dependencies===

Volumes

===Known bugs===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker.

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

== More Information ==

===Acknowledgment===
National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149 (to Ron Kikinis, Marek Kubicki).

===References===
* [http://lmi.bwh.harvard.edu/papers/pdfs/2002/bjornemoMICCAI02.pdf Björnemo M, Brun A, Kikinis R, Westin CF. Regularized stochastic white matter tractography using diffusion tensor MRI. In Fifth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI'02). Tokyo, Japan, 2002;435-442.]
* [http://lmi.bwh.harvard.edu/papers/pdfs/2006/frimanTMI06.pdf Friman, O., Farneback, G., Westin CF. A Bayesian Approach for Stochastic White Matter Tractography. IEEE Transactions on Medical Imaging, Vol 25, No. 8, Aug. 2006]
* [http://www.na-mic.org/Wiki/index.php/Image:IC_posternew.png Shenton, M.E., Ngo, T., Rosenberger, G., Westin, C.F., Levitt, J.J., McCarley, R.W., Kubicki, M. Study of Thalamo-Cortical White Matter Fiber Tract Projections in Schizophrenia Using Diffusion Stochastic Tractography. Poster presented at the 46th Meeting of the American College of Neuropsychopharmacology, Boca Raton, FL, December 2007.]

Modules:StochasticTractography-Documentation-3.4

2009-04-16T01:13:59Z

Jvs:

[[Documentation-3.4|Return to Slicer 3.4 Documentation]]
__NOTOC__
===Module Name===
Stochastic Tractography

{|
|[[Image:Cc_01.png|thumb|280px|Corpus callosum with stochastic tractography]]
|[[Image:Cc_stoch.png|thumb|280px|Corpus callosum lateral projections]]
|}

== General Information ==
===Module Type & Category===

Type: Interactive

Category: DTI

===Authors, Collaborators & Contact===
* Author: Julien von Siebenthal
* Contributor: Steve Pieper
* Contact: jvs@bwh.harvard.edu

===Module Description===
As a main purpose, the stochastic tractography module helps to evaluate connectivity between two regions of interest (ROIs) of the brain. These ROIs define generally grey matter regions having a specific neurophysiological function. Extensively, study involving more than two regions could still be done by pairing the regions two by two.

== Usage ==
* You want to study fiber path from a single region of interest (ROI)
* You want to evaluate connectivity between two ROIs

=== Description ===

{|
|[[Image:General.png|thumb|1000px|Stochastic tractography panel]]
|}

With the stochastic tractography module, you can:
{|
|
* Feature 1 : smooth the given Diffusion Weighted Image (DWI) using a Half Width Full Maximum gaussian filter
[[Image:smooth2.png|thumb|500px|Smoothing step]]
|}

{|
|
* Feature 2 : generate a brain mask from the DWI baseline input
[[Image:mask2.png|thumb|500px|Brain mask step]]
|}

{|
|
* Feature 3 : create a DTI (Diffusion Tensor Image) tensor from the DWI input
{|
|[[Image:tensor2.png|thumb|500px|Tensor step]]
|}
|}

{|
|
* Feature 4 : produce different measures based on the tensor like fractional anistropy (FA), mode and trace
{|
|[[Image:fa2.png|thumb|500px|Tensor step: FA]]
|[[Image:mode2.png|thumb|500px|Tensor step: mode]]
|[[Image:trace2.png|thumb|500px|Tensor step: trace]]
|}
|}

{|
|
* Feature 5 : produce connection maps in case 2 ROIs are given without ROI filtering from the tractography
** showing union and intersection of both maps from region A to region B and B to A
{|
|[[Image:AorB2.png|thumb|500px|Union of A to B and B to A]]
|[[Image:AandB2.png|thumb|500px|Intersection of A to B and B to A]]
|}
|}

{|
|
* Feature 6 : produce connection maps in case 2 ROIs are given with ROI filtering from the tractography
** showing only tracts connecting region A to region B and B to A
{|
|[[Image:connectAB2.png|thumb|500px|ROI filtering]]
|[[Image:A2B2.png|thumb|500px|ROI filtering from A to B]]
|[[Image:B2A2.png|thumb|500px|ROI filtering from B to A]]
|}
|}

* [http://www.na-mic.org/Wiki/index.php/Python_Stochastic_Tractography_Tutorial link tutorial]
===Quick Tour of Features and Use===

{|
|
* '''IO panel:'''
** Input DWI Volume: the DWI is loaded through the Volume module - it is th only mandatory input.
** Input ROI Volume (A/B): only 1 ROI is needed to achieve a tractography. If you want to evaluate the connection between two regions, you will give both ROIs.
** Input WM Volume: a white matter mask can be given as input to use ones provided by other tools or Slicer modules - it will supersede the brain mask even if enabled. Be mindful in setting a WM: tractography results can be impaired by a too restrictive WM.
** You are not obliged to set the ROIs or the white matter mask to smooth the DWI, create the brain mask and the tensor. These 3 steps just require a DWI.
{|
|[[Image:IOmenu.png|thumb|500px|IO step]]
|}
|}

{|
|
* '''Smoothing panel:'''
** Gaussian FWHM: this filter defines a Full Width Half Maximum. You can define it for each direction in modifying each component of the 3-vector.
** Advice: you can enable solely that functionality and compute several times with different parameters till satisfaction.
{|
|[[Image:Smoothmenu.png|thumb|500px|Smoothing step]]
|}
|}

{|
|
* '''Brain Mask panel:'''
** Lower/Higher Brain Threshold: this filter is based on a simple level set segmentation - intensities of the baseline lying between the two values will be represented, others are set to 0. The most common use of this filter is to remove ventricles from the tractography domain and most of the outside of the brain.
** Advice: you can enable solely that functionality and compute several times with different parameters till satisfaction.
{|
|[[Image:Maskmenu.png|thumb|500px|Brain mask step]]
|}
|}

{|
|
* '''Diffusion Tensor panel:'''
** Important: this step is not mandatory. It is here to evaluate the whole tensor and achieve measurements like FA, mode or trace. You did not need it to achieve tractography.
** FA, mode and trace are sent as scalar volumes and inserted in the MRML tree to be further used.
** Advice: you can enable solely that functionality and compute several times with different parameters till satisfaction.
{|
|[[Image:Tensormenu.png|thumb|500px|Tensor step]]
|}
|}

{|
|
* '''Tractography panel:''' This panel deals with the tractography per se:
** Total tracts: number of generated tracts per voxel.
** Maximum tract length (mm): set the maximum length a tract could reach.
** Step size (mm): is the step length for the update vector.
** Use spacing: must be used with caution - activate spacing of the update vector.
** Stopping criteria: FA is used as the stopping criteria. Advice: as ROIs are defined in the grey matter FA are generally very low, therefore do not use it in most cases.
{|
|[[Image:Tractomenu.png|thumb|500px|Tractography step]]
|}
|}

{|
|
* '''Connectivity Map panel:''' This panel lets the user modify parameters to create density/connectivity maps. A map is a scalar volume storing the number of times each voxel is traversed by tracts. It can be counted differently which is the purpose of the following parameters:
** Computation mode:
*** binary: voxel counter is incremented by 1 only once
*** cumulative: voxel counter is incremented by 1 each time a tract traverses it
*** weighted: same as cumulative but the increment is the length of the tract traversing the voxel
** Length based: must be enabled if the resulting tracts must be subdivided related to their length ownership
*** dThird: tracts only counted have length between 1 and (maximum tract length)/3
*** mThird: tracts only counted have length between (maximum tract length)/3 and 2 * (maximum tract length)/3
*** uThird: tracts only counted have length between 2 * (maximum tract length)/3 and (maximum tract length)
{|
|[[Image:Connectmenu.png|thumb|500px|Connectivity step]]
|}
|}

== Development ==

===Dependencies===

Volumes

===Known bugs===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker.

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

== More Information ==

===Acknowledgment===
National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149 (to Ron Kikinis, Marek Kubicki).

===References===
* [http://lmi.bwh.harvard.edu/papers/pdfs/2002/bjornemoMICCAI02.pdf Björnemo M, Brun A, Kikinis R, Westin CF. Regularized stochastic white matter tractography using diffusion tensor MRI. In Fifth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI'02). Tokyo, Japan, 2002;435-442.]
* [http://lmi.bwh.harvard.edu/papers/pdfs/2006/frimanTMI06.pdf Friman, O., Farneback, G., Westin CF. A Bayesian Approach for Stochastic White Matter Tractography. IEEE Transactions on Medical Imaging, Vol 25, No. 8, Aug. 2006]
* [http://www.na-mic.org/Wiki/index.php/Image:IC_posternew.png Shenton, M.E., Ngo, T., Rosenberger, G., Westin, C.F., Levitt, J.J., McCarley, R.W., Kubicki, M. Study of Thalamo-Cortical White Matter Fiber Tract Projections in Schizophrenia Using Diffusion Stochastic Tractography. Poster presented at the 46th Meeting of the American College of Neuropsychopharmacology, Boca Raton, FL, December 2007.]

Modules:StochasticTractography-Documentation-3.4

2009-04-16T01:10:40Z

Jvs:

[[Documentation-3.4|Return to Slicer 3.4 Documentation]]
__NOTOC__
===Module Name===
Stochastic Tractography

{|
|[[Image:Cc_01.png|thumb|280px|Corpus callosum with stochastic tractography]]
|[[Image:Cc_stoch.png|thumb|280px|Corpus callosum lateral projections]]
|}

== General Information ==
===Module Type & Category===

Type: Interactive

Category: DTI

===Authors, Collaborators & Contact===
* Author: Julien von Siebenthal
* Contributor: Steve Pieper
* Contact: jvs@bwh.harvard.edu

===Module Description===
As a main purpose, the stochastic tractography module helps to evaluate connectivity between two regions of interest (ROIs) of the brain. These ROIs define generally grey matter regions having a specific neurophysiological function. Extensively, study involving more than two regions could still be done by pairing the regions two by two.

== Usage ==
* You want to study fiber path from a single region of interest (ROI)
* You want to evaluate connectivity between two ROIs

=== Description ===

{|
|[[Image:General.png|thumb|1000px|Stochastic tractography panel]]
|}

With the stochastic tractography module, you can:
{|
|
* Feature 1 : smooth using a Half Width Full Maximum gaussian filter
[[Image:smooth2.png|thumb|500px|Smoothing step]]
|}

{|
|
* Feature 2 : generate a brain mask
[[Image:mask2.png|thumb|500px|Brain mask step]]
|}

{|
|
* Feature 3 : create a DTI (Diffusion Tensor Image) tensor
{|
|[[Image:tensor2.png|thumb|500px|Tensor step]]
|}
|}

{|
|
* Feature 4 : produce different measures based on the tensor like fractional anistropy (FA), mode and trace
{|
|[[Image:fa2.png|thumb|500px|Tensor step: FA]]
|[[Image:mode2.png|thumb|500px|Tensor step: mode]]
|[[Image:trace2.png|thumb|500px|Tensor step: trace]]
|}
|}

{|
|
* Feature 5 : produce connection maps in case 2 ROIs are given without ROI filtering
** showing union and intersection of both maps from region A to region B and B to A
{|
|[[Image:AorB2.png|thumb|500px|Union of A to B and B to A]]
|[[Image:AandB2.png|thumb|500px|Intersection of A to B and B to A]]
|}
|}

{|
|
* Feature 6 : produce connection maps in case 2 ROIs are given with ROI filtering
** showing only tracts connecting region A to region B and B to A
{|
|[[Image:connectAB2.png|thumb|500px|ROI filtering]]
|[[Image:A2B2.png|thumb|500px|ROI filtering from A to B]]
|[[Image:B2A2.png|thumb|500px|ROI filtering from B to A]]
|}
|}

* [http://www.na-mic.org/Wiki/index.php/Python_Stochastic_Tractography_Tutorial link tutorial]
===Quick Tour of Features and Use===

{|
|
* '''IO panel:'''
** Input DWI Volume: the DWI is loaded through the Volume module - it is th only mandatory input.
** Input ROI Volume (A/B): only 1 ROI is needed to achieve a tractography. If you want to evaluate the connection between two regions, you will give both ROIs.
** Input WM Volume: a white matter mask can be given as input to use ones provided by other tools or Slicer modules - it will supersede the brain mask even if enabled. Be mindful in setting a WM: tractography results can be impaired by a too restrictive WM.
** You are not obliged to set the ROIs or the white matter mask to smooth the DWI, create the brain mask and the tensor. These 3 steps just require a DWI.
{|
|[[Image:IOmenu.png|thumb|500px|IO step]]
|}
|}

{|
|
* '''Smoothing panel:'''
** Gaussian FWHM: this filter defines a Full Width Half Maximum. You can define it for each direction in modifying each component of the 3-vector.
** Advice: you can enable solely that functionality and compute several times with different parameters till satisfaction.
{|
|[[Image:Smoothmenu.png|thumb|500px|Smoothing step]]
|}
|}

{|
|
* '''Brain Mask panel:'''
** Lower/Higher Brain Threshold: this filter is based on a simple level set segmentation - intensities of the baseline lying between the two values will be represented, others are set to 0. The most common use of this filter is to remove ventricles from the tractography domain and most of the outside of the brain.
** Advice: you can enable solely that functionality and compute several times with different parameters till satisfaction.
{|
|[[Image:Maskmenu.png|thumb|500px|Brain mask step]]
|}
|}

{|
|
* '''Diffusion Tensor panel:'''
** Important: this step is not mandatory. It is here to evaluate the whole tensor and achieve measurements like FA, mode or trace. You did not need it to achieve tractography.
** FA, mode and trace are sent as scalar volumes and inserted in the MRML tree to be further used.
** Advice: you can enable solely that functionality and compute several times with different parameters till satisfaction.
{|
|[[Image:Tensormenu.png|thumb|500px|Tensor step]]
|}
|}

{|
|
* '''Tractography panel:''' This panel deals with the tractography per se:
** Total tracts: number of generated tracts per voxel.
** Maximum tract length (mm): set the maximum length a tract could reach.
** Step size (mm): is the step length for the update vector.
** Use spacing: must be used with caution - activate spacing of the update vector.
** Stopping criteria: FA is used as the stopping criteria. Advice: as ROIs are defined in the grey matter FA are generally very low, therefore do not use it in most cases.
{|
|[[Image:Tractomenu.png|thumb|500px|Tractography step]]
|}
|}

{|
|
* '''Connectivity Map panel:''' This panel lets the user modify parameters to create density/connectivity maps. A map is a scalar volume storing the number of times each voxel is traversed by tracts. It can be counted differently which is the purpose of the following parameters:
** Computation mode:
*** binary: voxel counter is incremented by 1 only once
*** cumulative: voxel counter is incremented by 1 each time a tract traverses it
*** weighted: same as cumulative but the increment is the length of the tract traversing the voxel
** Length based: must be enabled if the resulting tracts must be subdivided related to their length ownership
*** dThird: tracts only counted have length between 1 and (maximum tract length)/3
*** mThird: tracts only counted have length between (maximum tract length)/3 and 2 * (maximum tract length)/3
*** uThird: tracts only counted have length between 2 * (maximum tract length)/3 and (maximum tract length)
{|
|[[Image:Connectmenu.png|thumb|500px|Connectivity step]]
|}
|}

== Development ==

===Dependencies===

Volumes

===Known bugs===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker.

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

== More Information ==

===Acknowledgment===
National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149 (to Ron Kikinis, Marek Kubicki).

===References===
* [http://lmi.bwh.harvard.edu/papers/pdfs/2002/bjornemoMICCAI02.pdf Björnemo M, Brun A, Kikinis R, Westin CF. Regularized stochastic white matter tractography using diffusion tensor MRI. In Fifth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI'02). Tokyo, Japan, 2002;435-442.]
* [http://lmi.bwh.harvard.edu/papers/pdfs/2006/frimanTMI06.pdf Friman, O., Farneback, G., Westin CF. A Bayesian Approach for Stochastic White Matter Tractography. IEEE Transactions on Medical Imaging, Vol 25, No. 8, Aug. 2006]
* [http://www.na-mic.org/Wiki/index.php/Image:IC_posternew.png Shenton, M.E., Ngo, T., Rosenberger, G., Westin, C.F., Levitt, J.J., McCarley, R.W., Kubicki, M. Study of Thalamo-Cortical White Matter Fiber Tract Projections in Schizophrenia Using Diffusion Stochastic Tractography. Poster presented at the 46th Meeting of the American College of Neuropsychopharmacology, Boca Raton, FL, December 2007.]

Modules:StochasticTractography-Documentation-3.4

2009-04-16T01:08:22Z

Jvs:

[[Documentation-3.4|Return to Slicer 3.4 Documentation]]
__NOTOC__
===Module Name===
Stochastic Tractography

{|
|[[Image:Cc_01.png|thumb|280px|Corpus callosum with stochastic tractography]]
|[[Image:Cc_stoch.png|thumb|280px|Corpus callosum lateral projections]]
|}

== General Information ==
===Module Type & Category===

Type: Interactive

Category: DTI

===Authors, Collaborators & Contact===
* Author: Julien von Siebenthal
* Contributor: Steve Pieper
* Contact: jvs@bwh.harvard.edu

===Module Description===
As a main purpose, the stochastic tractography module helps to evaluate connectivity between two regions of interest (ROIs) of the brain. These ROIs define generally grey matter regions having a specific neurophysiological function. Extensively, study involving more than two regions could still be done by pairing the regions two by two.

== Usage ==
* You want to study fiber path from a single region of interest (ROI)
* You want to evaluate connectivity between two ROIs

=== Description ===

{|
|[[Image:General.png|thumb|1000px|Stochastic tractography panel]]
|}

With the stochastic tractography module, you can:
{|
|
* Feature 1 : smooth using a Half Width Full Maximum gaussian filter
[[Image:smooth2.png|thumb|500px|Smoothing step]]
|}

{|
|
* Feature 2 : generate a brain mask
[[Image:mask2.png|thumb|500px|Brain mask step]]
|}

{|
|
* Feature 3 : create a DTI (Diffusion Tensor Image) tensor
{|
|[[Image:tensor2.png|thumb|500px|Tensor step]]
|}
|}

{|
|
* Feature 4 : produce different measures based on the tensor like fractional anistropy (FA), mode and trace
{|
|[[Image:fa2.png|thumb|500px|Tensor step: FA]]
|[[Image:mode2.png|thumb|500px|Tensor step: mode]]
|[[Image:trace2.png|thumb|500px|Tensor step: trace]]
|}
|}

{|
|
* Feature 5 : produce connection maps in case 2 ROIs are given without ROI filtering
** showing union and intersection of both maps from region A to region B and B to A
{|
|[[Image:AorB2.png|thumb|500px|Union of A to B and B to A]]
|[[Image:AandB2.png|thumb|500px|Intersection of A to B and B to A]]
|}
|}

{|
|
* Feature 6 : produce connection maps in case 2 ROIs are given with ROI filtering
** showing only tracts connecting region A to region B and B to A
{|
|[[Image:connectAB2.png|thumb|500px|ROI filtering]]
|[[Image:A2B2.png|thumb|500px|ROI filtering from A to B]]
|[[Image:B2A2.png|thumb|500px|ROI filtering from B to A]]
|}
|}

* [http://www.na-mic.org/Wiki/index.php/Python_Stochastic_Tractography_Tutorial link tutorial]
===Quick Tour of Features and Use===

{|
|
* '''IO panel:'''
** Input DWI Volume: the DWI is loaded through the Volume module - it is th only mandatory input.
** Input ROI Volume (A/B): only 1 ROI is needed to achieve a tractography. If you want to evaluate the connection between two regions, you will give both ROIs.
** Input WM Volume: a white matter mask can be given as input to use ones provided by other tools or Slicer modules - it will supersede the brain mask even if enabled. Be mindful in setting a WM: tractography results can be impaired by a too restrictive WM.
** You are not obliged to set the ROIs or the white matter mask to smooth the DWI, create the brain mask and the tensor. These 3 steps just require a DWI.
{|
|[[Image:IOmenu.png|thumb|500px|IO step]]
|}
|}

{|
|
* '''Smoothing panel:'''
** Gaussian FWHM: this filter defines a Full Width Half Maximum. You can define it for each direction in modifying each component of the 3-vector.
** Advice: you can enable solely that functionality and compute several times with different parameters till satisfaction.
{|
|[[Image:Smoothmenu.png|thumb|500px|Smoothing step]]
|}
|}

{|
|
* '''Brain Mask panel:'''
** Lower/Higher Brain Threshold: this filter is based on a simple level set segmentation - intensities of the baseline lying between the two values will be represented, others are set to 0. The most common use of this filter is to remove ventricles from the tractography domain and most of the outside of the brain.
** Advice: you can enable solely that functionality and compute several times with different parameters till satisfaction.
{|
|[[Image:Maskmenu.png|thumb|500px|Brain mask step]]
|}
|}

{|
|
* '''Diffusion Tensor panel:'''
** Important: this step is not mandatory. It is here to evaluate the whole tensor and achieve measurements like FA, mode or trace. You did not need it to achieve tractography.
** FA, mode and trace are sent as scalar volumes and inserted in the MRML tree to be further used.
** Advice: you can enable solely that functionality and compute several times with different parameters till satisfaction.
{|
|[[Image:Tensormenu.png|thumb|500px|Tensor step]]
|}
|}

{|
|
* '''Tractography panel:''' This panel deals with the tractography per se:
** Total tracts: number of generated tracts per voxel.
** Maximum tract length (mm): set the maximum length a tract could reach.
** Step size (mm): is the step length for the update vector.
** Use spacing: must be used with caution - activate spacing of the update vector.
** Stopping criteria: FA is used as the stopping criteria. Advice: as ROIs are defined in the grey matter FA are generally very low, therefore do not use it in most cases.
{|
|[[Image:Tractomenu.png|thumb|500px|Tractography step]]
|}
|}

{|
|
* '''Connectivity Map panel:''' This panel lets the user modify parameters to create density/connectivity maps. A map is a scalar volume storing the number of times each voxel is traversed by tracts. It can be counted differently which the purpose of the following parameters:
** Computation mode:
*** binary: voxel counter is incremented by 1 only once
*** cumulative: voxel counter is incremented by 1 each time a tract traverses it
*** weighted: same as cumulative but the increment is the length of the tract traversing the voxel
** Length based: must be enabled if the resulting tracts must be subdivided related to their length ownership
*** dThird: tracts only counted have length between 1 and (maximum tract length)/3
*** mThird: tracts only counted have length between (maximum tract length)/3 and 2 * (maximum tract length)/3
*** uThird: tracts only counted have length between 2 * (maximum tract length)/3 and (maximum tract length)
{|
|[[Image:Connectmenu.png|thumb|500px|Connectivity step]]
|}
|}

== Development ==

===Dependencies===

Volumes

===Known bugs===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker.

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

== More Information ==

===Acknowledgment===
National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149 (to Ron Kikinis, Marek Kubicki).

===References===
* [http://lmi.bwh.harvard.edu/papers/pdfs/2002/bjornemoMICCAI02.pdf Björnemo M, Brun A, Kikinis R, Westin CF. Regularized stochastic white matter tractography using diffusion tensor MRI. In Fifth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI'02). Tokyo, Japan, 2002;435-442.]
* [http://lmi.bwh.harvard.edu/papers/pdfs/2006/frimanTMI06.pdf Friman, O., Farneback, G., Westin CF. A Bayesian Approach for Stochastic White Matter Tractography. IEEE Transactions on Medical Imaging, Vol 25, No. 8, Aug. 2006]
* [http://www.na-mic.org/Wiki/index.php/Image:IC_posternew.png Shenton, M.E., Ngo, T., Rosenberger, G., Westin, C.F., Levitt, J.J., McCarley, R.W., Kubicki, M. Study of Thalamo-Cortical White Matter Fiber Tract Projections in Schizophrenia Using Diffusion Stochastic Tractography. Poster presented at the 46th Meeting of the American College of Neuropsychopharmacology, Boca Raton, FL, December 2007.]

Modules:StochasticTractography-Documentation-3.4

2009-04-16T01:06:31Z

Jvs:

[[Documentation-3.4|Return to Slicer 3.4 Documentation]]
__NOTOC__
===Module Name===
Stochastic Tractography

{|
|[[Image:Cc_01.png|thumb|280px|Corpus callosum with stochastic tractography]]
|[[Image:Cc_stoch.png|thumb|280px|Corpus callosum lateral projections]]
|}

== General Information ==
===Module Type & Category===

Type: Interactive

Category: DTI

===Authors, Collaborators & Contact===
* Author: Julien von Siebenthal
* Contributor: Steve Pieper
* Contact: jvs@bwh.harvard.edu

===Module Description===
As a main purpose, the stochastic tractography module helps to evaluate connectivity between two regions of interest (ROIs) of the brain. These ROIs define generally grey matter regions having a specific neurophysiological function. Extensively, study involving more than two regions could still be done by pairing the regions two by two.

== Usage ==
* You want to study fiber path from a single region of interest (ROI)
* You want to evaluate connectivity between two ROIs

=== Description ===

{|
|[[Image:General.png|thumb|1000px|Stochastic tractography panel]]
|}

With the stochastic tractography module, you can:
{|
|
* Feature 1 : smooth using a Half Width Full Maximum gaussian filter
[[Image:smooth2.png|thumb|500px|Smoothing step]]
|}

{|
|
* Feature 2 : generate a brain mask
[[Image:mask2.png|thumb|500px|Brain mask step]]
|}

{|
|
* Feature 3 : create a DTI (Diffusion Tensor Image) tensor
{|
|[[Image:tensor2.png|thumb|500px|Tensor step]]
|}
|}

{|
|
* Feature 4 : produce different measures based on the tensor like fractional anistropy (FA), mode and trace
{|
|[[Image:fa2.png|thumb|500px|Tensor step: FA]]
|[[Image:mode2.png|thumb|500px|Tensor step: mode]]
|[[Image:trace2.png|thumb|500px|Tensor step: trace]]
|}
|}

{|
|
* Feature 5 : produce connection maps in case 2 ROIs are given without ROI filtering
** showing union and intersection of both maps from region A to region B and B to A
{|
|[[Image:AorB2.png|thumb|500px|Union of A to B and B to A]]
|[[Image:AandB2.png|thumb|500px|Intersection of A to B and B to A]]
|}
|}

{|
|
* Feature 6 : produce connection maps in case 2 ROIs are given with ROI filtering
** showing only tracts connecting region A to region B and B to A
{|
|[[Image:connectAB2.png|thumb|500px|ROI filtering]]
|[[Image:A2B2.png|thumb|500px|ROI filtering from A to B]]
|[[Image:B2A2.png|thumb|500px|ROI filtering from B to A]]
|}
|}

* [http://www.na-mic.org/Wiki/index.php/Python_Stochastic_Tractography_Tutorial link tutorial]
===Quick Tour of Features and Use===

{|
|
* '''IO panel:'''
** Input DWI Volume: the DWI is loaded through the Volume module - it is th only mandatory input.
** Input ROI Volume (A/B): only 1 ROI is needed to achieve a tractography. If you want to evaluate the connection between two regions, you will give both ROIs.
** Input WM Volume: a white matter mask can be given as input to use ones provided by other tools or Slicer modules - it will supersede the brain mask even if enabled. Be mindful in setting a WM: tractography results can be impaired by a too restrictive WM.
** You are not obliged to set the ROIs or the white matter mask to smooth the DWI, create the brain mask and the tensor. These 3 steps just require a DWI.
{|
|[[Image:IOmenu.png|thumb|500px|IO step]]
|}
|}

{|
|
* '''Smoothing panel:'''
** Gaussian FWHM: this filter defines a Full Width Half Maximum. You can define it for each direction in modifying each component of the 3-vector.
** Advice: you can enable solely that functionality and compute several times with different parameters till you're satisfied with the output.
{|
|[[Image:Smoothmenu.png|thumb|500px|Smoothing step]]
|}
|}

{|
|
* '''Brain Mask panel:'''
** Lower/Higher Brain Threshold: this filter is based on a simple level set segmentation - intensities of the baseline lying between the two values will be represented, others are set to 0. The most common use of this filter is to remove ventricles from the tractography domain and most of the outside of the brain.
{|
|[[Image:Maskmenu.png|thumb|500px|Brain mask step]]
|}
|}

{|
|
* '''Diffusion Tensor panel:'''
** Important: this step is not mandatory. It is here to evaluate the whole tensor and achieve measurements like FA, mode or trace. You did not need it to achieve tractography.
** FA, mode and trace are sent as scalar volumes and inserted in the MRML tree to be further used.
{|
|[[Image:Tensormenu.png|thumb|500px|Tensor step]]
|}
|}

{|
|
* '''Tractography panel:''' This panel deals with the tractography per se:
** Total tracts: number of generated tracts per voxel.
** Maximum tract length (mm): set the maximum length a tract could reach.
** Step size (mm): is the step length for the update vector.
** Use spacing: must be used with caution - activate spacing of the update vector.
** Stopping criteria: FA is used as the stopping criteria. Advice: as ROIs are defined in the grey matter FA are generally very low, therefore do not use it in most cases.
{|
|[[Image:Tractomenu.png|thumb|500px|Tractography step]]
|}
|}

{|
|
* '''Connectivity Map panel:''' This panel lets the user modify parameters to create density/connectivity maps. A map is a scalar volume storing the number of times each voxel is traversed by tracts. It can be counted differently which the purpose of the following parameters:
** Computation mode:
*** binary: voxel counter is incremented by 1 only once
*** cumulative: voxel counter is incremented by 1 each time a tract traverses it
*** weighted: same as cumulative but the increment is the length of the tract traversing the voxel
** Length based: must be enabled if the resulting tracts must be subdivided related to their length ownership
*** dThird: tracts only counted have length between 1 and (maximum tract length)/3
*** mThird: tracts only counted have length between (maximum tract length)/3 and 2 * (maximum tract length)/3
*** uThird: tracts only counted have length between 2 * (maximum tract length)/3 and (maximum tract length)
{|
|[[Image:Connectmenu.png|thumb|500px|Connectivity step]]
|}
|}

== Development ==

===Dependencies===

Volumes

===Known bugs===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker.

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

== More Information ==

===Acknowledgment===
National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149 (to Ron Kikinis, Marek Kubicki).

===References===
* [http://lmi.bwh.harvard.edu/papers/pdfs/2002/bjornemoMICCAI02.pdf Björnemo M, Brun A, Kikinis R, Westin CF. Regularized stochastic white matter tractography using diffusion tensor MRI. In Fifth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI'02). Tokyo, Japan, 2002;435-442.]
* [http://lmi.bwh.harvard.edu/papers/pdfs/2006/frimanTMI06.pdf Friman, O., Farneback, G., Westin CF. A Bayesian Approach for Stochastic White Matter Tractography. IEEE Transactions on Medical Imaging, Vol 25, No. 8, Aug. 2006]
* [http://www.na-mic.org/Wiki/index.php/Image:IC_posternew.png Shenton, M.E., Ngo, T., Rosenberger, G., Westin, C.F., Levitt, J.J., McCarley, R.W., Kubicki, M. Study of Thalamo-Cortical White Matter Fiber Tract Projections in Schizophrenia Using Diffusion Stochastic Tractography. Poster presented at the 46th Meeting of the American College of Neuropsychopharmacology, Boca Raton, FL, December 2007.]

Modules:StochasticTractography-Documentation-3.4

2009-04-16T01:04:13Z

Jvs:

[[Documentation-3.4|Return to Slicer 3.4 Documentation]]
__NOTOC__
===Module Name===
Stochastic Tractography

{|
|[[Image:Cc_01.png|thumb|280px|Corpus callosum with stochastic tractography]]
|[[Image:Cc_stoch.png|thumb|280px|Corpus callosum lateral projections]]
|}

== General Information ==
===Module Type & Category===

Type: Interactive

Category: DTI

===Authors, Collaborators & Contact===
* Author: Julien von Siebenthal
* Contributor: Steve Pieper
* Contact: jvs@bwh.harvard.edu

===Module Description===
As a main purpose, the stochastic tractography module helps to evaluate connectivity between two regions of interest (ROIs) of the brain. These ROIs define generally grey matter regions having a specific neurophysiological function. Extensively, study involving more than two regions could still be done by pairing the regions two by two.

== Usage ==
* You want to study fiber path from a single region of interest (ROI)
* You want to evaluate connectivity between two ROIs

=== Description ===

{|
|[[Image:General.png|thumb|1000px|Stochastic tractography panel]]
|}

With the stochastic tractography module, you can:
{|
|
* Feature 1 : smooth using a Half Width Full Maximum gaussian filter
[[Image:smooth2.png|thumb|500px|Smoothing step]]
|}

{|
|
* Feature 2 : generate a brain mask
[[Image:mask2.png|thumb|500px|Brain mask step]]
|}

{|
|
* Feature 3 : create a DTI (Diffusion Tensor Image) tensor
{|
|[[Image:tensor2.png|thumb|500px|Tensor step]]
|}
|}

{|
|
* Feature 4 : produce different measures based on the tensor like fractional anistropy (FA), mode and trace
{|
|[[Image:fa2.png|thumb|500px|Tensor step: FA]]
|[[Image:mode2.png|thumb|500px|Tensor step: mode]]
|[[Image:trace2.png|thumb|500px|Tensor step: trace]]
|}
|}

{|
|
* Feature 5 : produce connection maps in case 2 ROIs are given without ROI filtering
** showing union and intersection of both maps from region A to region B and B to A
{|
|[[Image:AorB2.png|thumb|500px|Union of A to B and B to A]]
|[[Image:AandB2.png|thumb|500px|Intersection of A to B and B to A]]
|}
|}

{|
|
* Feature 6 : produce connection maps in case 2 ROIs are given with ROI filtering
** showing only tracts connecting region A to region B and B to A
{|
|[[Image:connectAB2.png|thumb|500px|ROI filtering]]
|[[Image:A2B2.png|thumb|500px|ROI filtering from A to B]]
|[[Image:B2A2.png|thumb|500px|ROI filtering from B to A]]
|}
|}

* [http://www.na-mic.org/Wiki/index.php/Python_Stochastic_Tractography_Tutorial link tutorial]
===Quick Tour of Features and Use===

{|
|
* '''IO panel:'''
** Input DWI Volume: the DWI is loaded through the Volume module - it is th only mandatory input.
** Input ROI Volume (A/B): only 1 ROI is needed to achieve a tractography. If you want to evaluate the connection between two regions, you will give both ROIs.
** Input WM Volume: a white matter mask can be given as input to use ones provided by other tools or Slicer modules - it will supersede the brain mask even if enabled. Be mindful in setting a WM: tractography results can be impaired by a too restrictive WM.
** You are not obliged to set the ROIs or the white matter mask to smooth the DWI, create the brain mask and the tensor. These 3 steps just require a DWI.
{|
|[[Image:IOmenu.png|thumb|500px|IO step]]
|}
|}

{|
|
* '''Smoothing panel:'''
** Gaussian FWHM: this filter defines a Full Width Half Maximum. You can define it for each direction in modifying each component of the 3-vector.
** Advice: you can enable solely that functionality and compute several times with different parameters till you're satisfied with the output.
{|
|[[Image:Smoothmenu.png|thumb|500px|Smoothing step]]
|}
|}

{|
|
* '''Brain Mask panel:'''
** Lower/Higher Brain Threshold: this filter is based on a simple level set segmentation - intensities of the baseline lying between the two values will be represented, others are set to 0. The most common use of this filter is to remove ventricles from the tractography domain and most of the outside of the brain.
{|
|[[Image:Maskmenu.png|thumb|500px|Brain mask step]]
|}
|}

{|
|
* '''Diffusion Tensor panel:'''
** Important: this step is not mandatory. It is here to evaluate the whole tensor and achieve measurements like FA, mode or trace. You did not need it to achieve tractography.
** FA, mode and trace are sent as scalar volumes and inserted in the MRML tree to be further used.
{|
|[[Image:Tensormenu.png|thumb|500px|Tensor step]]
|}
|}

{|
|
* '''Tractography panel:'''
This panel deals with the tractography per se:
** Total tracts: number of generated tracts per voxel.
** Maximum tract length (mm): set the maximum length a tract could reach.
** Step size (mm): is the step length for the update vector.
** Use spacing: must be used with caution - activate spacing of the update vector.
** Stopping criteria: FA is used as the stopping criteria. Advice: as ROIs are defined in the grey matter FA are generally very low, therefore do not use it in most cases.
{|
|[[Image:Tractomenu.png|thumb|500px|Tractography step]]
|}
|}

{|
|
* '''Connectivity Map panel:'''
This panel lets the user modify parameters to create density/connectivity maps. A map is a scalar volume storing the number of times each voxel is traversed by tracts. It can be counted differently which the purpose of the following parameters:
** Computation mode:
*** binary: voxel counter is incremented by 1 only once
*** cumulative: voxel counter is incremented by 1 each time a tract traverses it
*** weighted: same as cumulative but the increment is the length of the tract traversing the voxel
** Length based: must be enabled if the resulting tracts must be subdivided related to their length ownership
*** dThird: tracts only counted have length between 1 and (maximum tract length)/3
*** mThird: tracts only counted have length between (maximum tract length)/3 and 2 * (maximum tract length)/3
*** uThird: tracts only counted have length between 2 * (maximum tract length)/3 and (maximum tract length)
{|
|[[Image:Connectmenu.png|thumb|500px|Connectivity step]]
|}
|}

== Development ==

===Dependencies===

Volumes

===Known bugs===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker.

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

== More Information ==

===Acknowledgment===
National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149 (to Ron Kikinis, Marek Kubicki).

===References===
* [http://lmi.bwh.harvard.edu/papers/pdfs/2002/bjornemoMICCAI02.pdf Björnemo M, Brun A, Kikinis R, Westin CF. Regularized stochastic white matter tractography using diffusion tensor MRI. In Fifth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI'02). Tokyo, Japan, 2002;435-442.]
* [http://lmi.bwh.harvard.edu/papers/pdfs/2006/frimanTMI06.pdf Friman, O., Farneback, G., Westin CF. A Bayesian Approach for Stochastic White Matter Tractography. IEEE Transactions on Medical Imaging, Vol 25, No. 8, Aug. 2006]
* [http://www.na-mic.org/Wiki/index.php/Image:IC_posternew.png Shenton, M.E., Ngo, T., Rosenberger, G., Westin, C.F., Levitt, J.J., McCarley, R.W., Kubicki, M. Study of Thalamo-Cortical White Matter Fiber Tract Projections in Schizophrenia Using Diffusion Stochastic Tractography. Poster presented at the 46th Meeting of the American College of Neuropsychopharmacology, Boca Raton, FL, December 2007.]

Modules:StochasticTractography-Documentation-3.4

2009-04-16T00:39:18Z

Jvs:

[[Documentation-3.4|Return to Slicer 3.4 Documentation]]
__NOTOC__
===Module Name===
Stochastic Tractography

{|
|[[Image:Cc_01.png|thumb|280px|Corpus callosum with stochastic tractography]]
|[[Image:Cc_stoch.png|thumb|280px|Corpus callosum lateral projections]]
|}

== General Information ==
===Module Type & Category===

Type: Interactive

Category: DTI

===Authors, Collaborators & Contact===
* Author: Julien von Siebenthal
* Contributor: Steve Pieper
* Contact: jvs@bwh.harvard.edu

===Module Description===
As a main purpose, the stochastic tractography module helps to evaluate connectivity between two regions of interest (ROIs) of the brain. These ROIs define generally grey matter regions having a specific neurophysiological function. Extensively, study involving more than two regions could still be done by pairing the regions two by two.

== Usage ==
* You want to study fiber path from a single region of interest (ROI)
* You want to evaluate connectivity between two ROIs

=== Description ===

{|
|[[Image:General.png|thumb|1000px|Stochastic tractography panel]]
|}

With the stochastic tractography module, you can:
{|
|
* Feature 1 : smooth using a Half Width Full Maximum gaussian filter
[[Image:smooth2.png|thumb|500px|Smoothing step]]
|}

{|
|
* Feature 2 : generate a brain mask
[[Image:mask2.png|thumb|500px|Brain mask step]]
|}

{|
|
* Feature 3 : create a DTI (Diffusion Tensor Image) tensor
{|
|[[Image:tensor2.png|thumb|500px|Tensor step]]
|}
|}

{|
|
* Feature 4 : produce different measures based on the tensor like fractional anistropy (FA), mode and trace
{|
|[[Image:fa2.png|thumb|500px|Tensor step: FA]]
|[[Image:mode2.png|thumb|500px|Tensor step: mode]]
|[[Image:trace2.png|thumb|500px|Tensor step: trace]]
|}
|}

{|
|
* Feature 5 : produce connection maps in case 2 ROIs are given without ROI filtering
** showing union and intersection of both maps from region A to region B and B to A
{|
|[[Image:AorB2.png|thumb|500px|Union of A to B and B to A]]
|[[Image:AandB2.png|thumb|500px|Intersection of A to B and B to A]]
|}
|}

{|
|
* Feature 6 : produce connection maps in case 2 ROIs are given with ROI filtering
** showing only tracts connecting region A to region B and B to A
{|
|[[Image:connectAB2.png|thumb|500px|ROI filtering]]
|[[Image:A2B2.png|thumb|500px|ROI filtering from A to B]]
|[[Image:B2A2.png|thumb|500px|ROI filtering from B to A]]
|}
|}

* [http://www.na-mic.org/Wiki/index.php/Python_Stochastic_Tractography_Tutorial link tutorial]
===Quick Tour of Features and Use===

{|
|
* '''IO panel:'''
** Input DWI Volume: the DWI is loaded through the Volume module - it is th only mandatory input.
** Input ROI Volume (A/B): only 1 ROI is needed to achieve a tractography. If you want to evaluate the connection between two regions, you will give both ROIs.
** Input WM Volume: a white matter mask can be given as input to use ones provided by other tools or Slicer modules - it will supersede the brain mask even if enabled. Be mindful in setting a WM: tractography results can be impaired by a too restrictive WM.
** You are not obliged to set the ROIs or the white matter mask to smooth the DWI, create the brain mask and the tensor. These 3 steps just require a DWI.
{|
|[[Image:IOmenu.png|thumb|500px|IO step]]
|}
|}

{|
|
* '''Smoothing panel:'''
** Gaussian FWHM: this filter defines a Full Width Half Maximum. You can define it for each direction in modifying each component of the 3-vector.
** Advice: you can enable solely that functionality and compute several times with different parameters till you're satisfied with the output.
{|
|[[Image:Smoothmenu.png|thumb|500px|Smoothing step]]
|}
|}

{|
|
* '''Brain Mask panel:'''
** Lower/Higher Brain Threshold: this filter is based on a simple level set segmentation - intensities of the baseline lying between the two values will be represented, others are set to 0.
This filter allows to remove ventricles from the tractography domain and most of the outside of the brain. This impacts positively the speed without impairing the tractography.
{|
|[[Image:Maskmenu.png|thumb|500px|Brain mask step]]
|}
|}

{|
|
* '''Diffusion Tensor panel:'''
**Important: this step is not mandatory. It is here to evaluate the whole tensor and achieve measurements like FA, mode or trace. You did not need it to achieve tractography.
** FA, mode and trace are sent as scalar volumes and inserted in the MRML tree.
{|
|[[Image:Tensormenu.png|thumb|500px|Tensor step]]
|}
|}

{|
|
* '''Tractography panel:'''
** Total tracts: number of generated tracts per voxel.
** Maximum tract length (mm): set the maximum length tracts could reach.
** Step size (mm): is the step length for the update vector.
** Use spacing: must be used with caution - activate spacing to the update vector.
** Stopping criteria: FA is used as the stopping criteria. Advice: as ROIs are defined in the grey matter FA are generally very low, therefore do not use generally.
{|
|[[Image:Tractomenu.png|thumb|500px|Tractography step]]
|}
|}

{|
|
* '''Connectivity Map panel:'''
{|
|[[Image:Connectmenu.png|thumb|500px|Connectivity step]]
|}
|}

== Development ==

===Dependencies===

Volumes

===Known bugs===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker.

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

== More Information ==

===Acknowledgment===
National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149 (to Ron Kikinis, Marek Kubicki).

===References===
* [http://lmi.bwh.harvard.edu/papers/pdfs/2002/bjornemoMICCAI02.pdf Björnemo M, Brun A, Kikinis R, Westin CF. Regularized stochastic white matter tractography using diffusion tensor MRI. In Fifth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI'02). Tokyo, Japan, 2002;435-442.]
* [http://lmi.bwh.harvard.edu/papers/pdfs/2006/frimanTMI06.pdf Friman, O., Farneback, G., Westin CF. A Bayesian Approach for Stochastic White Matter Tractography. IEEE Transactions on Medical Imaging, Vol 25, No. 8, Aug. 2006]
* [http://www.na-mic.org/Wiki/index.php/Image:IC_posternew.png Shenton, M.E., Ngo, T., Rosenberger, G., Westin, C.F., Levitt, J.J., McCarley, R.W., Kubicki, M. Study of Thalamo-Cortical White Matter Fiber Tract Projections in Schizophrenia Using Diffusion Stochastic Tractography. Poster presented at the 46th Meeting of the American College of Neuropsychopharmacology, Boca Raton, FL, December 2007.]

Modules:StochasticTractography-Documentation-3.4

2009-04-16T00:35:47Z

Jvs:

[[Documentation-3.4|Return to Slicer 3.4 Documentation]]
__NOTOC__
===Module Name===
Stochastic Tractography

{|
|[[Image:Cc_01.png|thumb|280px|Corpus callosum with stochastic tractography]]
|[[Image:Cc_stoch.png|thumb|280px|Corpus callosum lateral projections]]
|}

== General Information ==
===Module Type & Category===

Type: Interactive

Category: DTI

===Authors, Collaborators & Contact===
* Author: Julien von Siebenthal
* Contributor: Steve Pieper
* Contact: jvs@bwh.harvard.edu

===Module Description===
As a main purpose, the stochastic tractography module helps to evaluate connectivity between two regions of interest (ROIs) of the brain. These ROIs define generally grey matter regions having a specific neurophysiological function. Extensively, study involving more than two regions could still be done by pairing the regions two by two.

== Usage ==
* You want to study fiber path from a single region of interest (ROI)
* You want to evaluate connectivity between two ROIs

=== Description ===

{|
|[[Image:General.png|thumb|1000px|Stochastic tractography panel]]
|}

With the stochastic tractography module, you can:
{|
|
* Feature 1 : smooth using a Half Width Full Maximum gaussian filter
[[Image:smooth2.png|thumb|500px|Smoothing step]]
|}

{|
|
* Feature 2 : generate a brain mask
[[Image:mask2.png|thumb|500px|Brain mask step]]
|}

{|
|
* Feature 3 : create a DTI (Diffusion Tensor Image) tensor
{|
|[[Image:tensor2.png|thumb|500px|Tensor step]]
|}
|}

{|
|
* Feature 4 : produce different measures based on the tensor like fractional anistropy (FA), mode and trace
{|
|[[Image:fa2.png|thumb|500px|Tensor step: FA]]
|[[Image:mode2.png|thumb|500px|Tensor step: mode]]
|[[Image:trace2.png|thumb|500px|Tensor step: trace]]
|}
|}

{|
|
* Feature 5 : produce connection maps in case 2 ROIs are given without ROI filtering
** showing union and intersection of both maps from region A to region B and B to A
{|
|[[Image:AorB2.png|thumb|500px|Union of A to B and B to A]]
|[[Image:AandB2.png|thumb|500px|Intersection of A to B and B to A]]
|}
|}

{|
|
* Feature 6 : produce connection maps in case 2 ROIs are given with ROI filtering
** showing only tracts connecting region A to region B and B to A
{|
|[[Image:connectAB2.png|thumb|500px|ROI filtering]]
|[[Image:A2B2.png|thumb|500px|ROI filtering from A to B]]
|[[Image:B2A2.png|thumb|500px|ROI filtering from B to A]]
|}
|}

* [http://www.na-mic.org/Wiki/index.php/Python_Stochastic_Tractography_Tutorial link tutorial]
===Quick Tour of Features and Use===

{|
|
* '''IO panel:'''
** Input DWI Volume: the DWI is loaded through the Volume module - it is th only mandatory input.
** Input ROI Volume (A/B): only 1 ROI is needed to achieve a tractography. If you want to evaluate the connection between two regions, you will give both ROIs.
** Input WM Volume: a white matter mask can be given as input to use ones provided by other tools or Slicer modules - it will supersede the brain mask even if enabled. Be mindful in setting a WM: tractography results can be impaired by a too restrictive WM.
** You are not obliged to set the ROIs or the white matter mask to smooth the DWI, create the brain mask and the tensor. These 3 steps just require a DWI.
{|
|[[Image:IOmenu.png]]
|}
|}

{|
|
* '''Smoothing panel:'''
** Gaussian FWHM: this filter defines a Full Width Half Maximum. You can define it for each direction in modifying each component of the 3-vector.
** Advice: you can enable solely that functionality and compute several times with different parameters till you're satisfied with the output.
{|
|[[Image:Smoothmenu.png]]
|}
|}

{|
|
* '''Brain Mask panel:'''
** Lower/Higher Brain Threshold: this filter is based on a simple level set segmentation - intensities of the baseline lying between the two values will be represented, others are set to 0.
This filter allows to remove ventricles from the tractography domain and most of the outside of the brain. This impacts positively the speed without impairing the tractography.
{|
|[[Image:Maskmenu.png]]
|}
|}

{|
|
* '''Diffusion Tensor panel:'''
**Important: this step is not mandatory. It is here to evaluate the whole tensor and achieve measurements like FA, mode or trace. You did not need it to achieve tractography.
** FA, mode and trace are sent as scalar volumes and inserted in the MRML tree.
{|
|[[Image:Tensormenu.png]]
|}
|}

{|
|
* '''Tractography panel:'''
** Total tracts: number of generated tracts per voxel.
** Maximum tract length (mm): set the maximum length tracts could reach.
** Step size (mm): is the step length for the update vector.
** Use spacing: must be used with caution - activate spacing to the update vector.
** Stopping criteria: FA is used as the stopping criteria. Advice: as ROIs are defined in the grey matter FA are generally very low, therefore do not use generally.
{|
|[[Image:Tractomenu.png]]
|}
|}

{|
|
* '''Connectivity Map panel:'''
{|
|[[Image:Connectmenu.png]]
|}
|}

== Development ==

===Dependencies===

Volumes

===Known bugs===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker.

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

== More Information ==

===Acknowledgment===
National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149 (to Ron Kikinis, Marek Kubicki).

===References===
* [http://lmi.bwh.harvard.edu/papers/pdfs/2002/bjornemoMICCAI02.pdf Björnemo M, Brun A, Kikinis R, Westin CF. Regularized stochastic white matter tractography using diffusion tensor MRI. In Fifth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI'02). Tokyo, Japan, 2002;435-442.]
* [http://lmi.bwh.harvard.edu/papers/pdfs/2006/frimanTMI06.pdf Friman, O., Farneback, G., Westin CF. A Bayesian Approach for Stochastic White Matter Tractography. IEEE Transactions on Medical Imaging, Vol 25, No. 8, Aug. 2006]
* [http://www.na-mic.org/Wiki/index.php/Image:IC_posternew.png Shenton, M.E., Ngo, T., Rosenberger, G., Westin, C.F., Levitt, J.J., McCarley, R.W., Kubicki, M. Study of Thalamo-Cortical White Matter Fiber Tract Projections in Schizophrenia Using Diffusion Stochastic Tractography. Poster presented at the 46th Meeting of the American College of Neuropsychopharmacology, Boca Raton, FL, December 2007.]

Modules:StochasticTractography-Documentation-3.4

2009-04-16T00:32:29Z

Jvs:

[[Documentation-3.4|Return to Slicer 3.4 Documentation]]
__NOTOC__
===Module Name===
Stochastic Tractography

{|
|[[Image:Cc_01.png|thumb|280px|Corpus callosum with stochastic tractography]]
|[[Image:Cc_stoch.png|thumb|280px|Corpus callosum lateral projections]]
|}

== General Information ==
===Module Type & Category===

Type: Interactive

Category: DTI

===Authors, Collaborators & Contact===
* Author: Julien von Siebenthal
* Contributor: Steve Pieper
* Contact: jvs@bwh.harvard.edu

===Module Description===
As a main purpose, the stochastic tractography module helps to evaluate connectivity between two regions of interest (ROIs) of the brain. These ROIs define generally grey matter regions having a specific neurophysiological function. Extensively, study involving more than two regions could still be done by pairing the regions two by two.

== Usage ==
* You want to study fiber path from a single region of interest (ROI)
* You want to evaluate connectivity between two ROIs

=== Description ===

{|
|[[Image:General.png|thumb|1000px|Stochastic tractography panel]]
|}

With the stochastic tractography module, you can:
{|
|
* Feature 1 : smooth using a Half Width Full Maximum gaussian filter
[[Image:smooth2.png|thumb|500px|Smoothing step]]
|}

{|
|
* Feature 2 : generate a brain mask
[[Image:mask2.png|thumb|500px|Brain mask step]]
|}

{|
|
* Feature 3 : create a DTI (Diffusion Tensor Image) tensor
{|
|[[Image:tensor2.png|thumb|500px|Tensor step]]
|}
|}

{|
|
* Feature 4 : produce different measures based on the tensor like fractional anistropy (FA), mode and trace
{|
|[[Image:fa2.png|thumb|500px|Tensor step: FA]]
|[[Image:mode2.png|thumb|500px|Tensor step: mode]]
|[[Image:trace2.png|thumb|500px|Tensor step: trace]]
|}
|}

{|
|
* Feature 5 : produce connection maps in case 2 ROIs are given without ROI filtering
** showing union and intersection of both maps from region A to region B and B to A
{|
|[[Image:AorB2.png|thumb|500px|Union of A to B and B to A]]
|[[Image:AandB2.png|thumb|500px|Intersection of A to B and B to A]]
|}
|}

{|
|
* Feature 6 : produce connection maps in case 2 ROIs are given with ROI filtering
** showing only tracts connecting region A to region B and B to A
{|
|[[Image:connectAB2.png|thumb|500px|ROI filtering]]
|[[Image:A2B2.png|thumb|500px|ROI filtering from A to B]]
|[[Image:B2A2.png|thumb|500px|ROI filtering from B to A]]
|}
|}

* [http://www.na-mic.org/Wiki/index.php/Python_Stochastic_Tractography_Tutorial link tutorial]
===Quick Tour of Features and Use===

* '''IO panel:'''
** Input DWI Volume: the DWI is loaded through the Volume module - it is th only mandatory input.
** Input ROI Volume (A/B): only 1 ROI is needed to achieve a tractography. If you want to evaluate the connection between two regions, you will give both ROIs.
** Input WM Volume: a white matter mask can be given as input to use ones provided by other tools or Slicer modules - it will supersede the brain mask even if enabled. Be mindful in setting a WM: tractography results can be impaired by a too restrictive WM.
** You are not obliged to set the ROIs or the white matter mask to smooth the DWI, create the brain mask and the tensor. These 3 steps just require a DWI.
[[Image:IOmenu.png]]

* '''Smoothing panel:'''
** Gaussian FWHM: this filter defines a Full Width Half Maximum. You can define it for each direction in modifying each component of the 3-vector.
** Advice: you can enable solely that functionality and compute several times with different parameters till you're satisfied with the output.
[[Image:Smoothmenu.png]]

* '''Brain Mask panel:'''
** Lower/Higher Brain Threshold: this filter is based on a simple level set segmentation - intensities of the baseline lying between the two values will be represented, others are set to 0.
This filter allows to remove ventricles from the tractography domain and most of the outside of the brain. This impacts positively the speed without impairing the tractography.
[[Image:Maskmenu.png]]

* '''Diffusion Tensor panel:'''
**Important: this step is not mandatory. It is here to evaluate the whole tensor and achieve measurements like FA, mode or trace. You did not need it to achieve tractography.
** FA, mode and trace are sent as scalar volumes and inserted in the MRML tree.
[[Image:Tensormenu.png]]

* '''Tractography panel:'''
** Total tracts: number of generated tracts per voxel.
** Maximum tract length (mm): set the maximum length tracts could reach.
** Step size (mm): is the step length for the update vector.
** Use spacing: must be used with caution - activate spacing to the update vector.
** Stopping criteria: FA is used as the stopping criteria. Advice: as ROIs are defined in the grey matter FA are generally very low, therefore do not use generally.
[[Image:Tractomenu.png]]

* '''Connectivity Map panel:'''
[[Image:Connectmenu.png]]

== Development ==

===Dependencies===

Volumes

===Known bugs===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker.

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

== More Information ==

===Acknowledgment===
National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149 (to Ron Kikinis, Marek Kubicki).

===References===
* [http://lmi.bwh.harvard.edu/papers/pdfs/2002/bjornemoMICCAI02.pdf Björnemo M, Brun A, Kikinis R, Westin CF. Regularized stochastic white matter tractography using diffusion tensor MRI. In Fifth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI'02). Tokyo, Japan, 2002;435-442.]
* [http://lmi.bwh.harvard.edu/papers/pdfs/2006/frimanTMI06.pdf Friman, O., Farneback, G., Westin CF. A Bayesian Approach for Stochastic White Matter Tractography. IEEE Transactions on Medical Imaging, Vol 25, No. 8, Aug. 2006]
* [http://www.na-mic.org/Wiki/index.php/Image:IC_posternew.png Shenton, M.E., Ngo, T., Rosenberger, G., Westin, C.F., Levitt, J.J., McCarley, R.W., Kubicki, M. Study of Thalamo-Cortical White Matter Fiber Tract Projections in Schizophrenia Using Diffusion Stochastic Tractography. Poster presented at the 46th Meeting of the American College of Neuropsychopharmacology, Boca Raton, FL, December 2007.]

Modules:StochasticTractography-Documentation-3.4

2009-04-16T00:28:41Z

Jvs:

[[Documentation-3.4|Return to Slicer 3.4 Documentation]]
__NOTOC__
===Module Name===
Stochastic Tractography

{|
|[[Image:Cc_01.png|thumb|280px|Corpus callosum with stochastic tractography]]
|[[Image:Cc_stoch.png|thumb|280px|Corpus callosum lateral projections]]
|}

== General Information ==
===Module Type & Category===

Type: Interactive

Category: DTI

===Authors, Collaborators & Contact===
* Author: Julien von Siebenthal
* Contributor: Steve Pieper
* Contact: jvs@bwh.harvard.edu

===Module Description===
As a main purpose, the stochastic tractography module helps to evaluate connectivity between two regions of interest (ROIs) of the brain. These ROIs define generally grey matter regions having a specific neurophysiological function. Extensively, study involving more than two regions could still be done by pairing the regions two by two.

== Usage ==
* You want to study fiber path from a single region of interest (ROI)
* You want to evaluate connectivity between two ROIs

=== Description ===

{|
|[[Image:General.png|thumb|1000px|Stochastic tractography panel]]
|}

With the stochastic tractography module, you can:
{|
|
* Feature 1 : smooth using a Half Width Full Maximum gaussian filter
[[Image:smooth2.png|thumb|500px|Smoothing step]]
|}

{|
|
* Feature 2 : generate a brain mask
[[Image:mask2.png|thumb|500px|Brain mask step]]
|}

{|
|
* Feature 3 : create a DTI (Diffusion Tensor Image) tensor
{|
|[[Image:tensor2.png|thumb|500px|Tensor step]]
|}
|}

{|
|
* Feature 4 : produce different measures based on the tensor like fractional anistropy (FA), mode and trace
{|
|[[Image:fa2.png|thumb|500px|Tensor step: FA]]
|[[Image:mode2.png|thumb|500px|Tensor step: mode]]
|[[Image:trace2.png|thumb|500px|Tensor step: trace]]
|}
|}

{|
|
* Feature 5 : produce connection maps in case 2 ROIs are given without ROI filtering
** showing union and intersection of both maps from region A to region B and B to A
{|
|[[Image:AorB2.png|thumb|500px|Union of A to B and B to A]]
|[[Image:AandB2.png|thumb|500px|Intersection of A to B and B to A]]
|}
|}

{|
|
* Feature 6 : produce connection maps in case 2 ROIs are given with ROI filtering
** showing only tracts connecting region A to region B and B to A
{|
|[[Image:connectAB2.png|thumb|500px|ROI filtering]]
|[[Image:A2B2.png|thumb|500px|ROI filtering from A to B]]
|[[Image:B2A2.png|thumb|500px|ROI filtering from B to A]]
|}
|}

* [http://www.na-mic.org/Wiki/index.php/Python_Stochastic_Tractography_Tutorial link tutorial]
===Quick Tour of Features and Use===

* '''IO panel:'''
[[Image:IOmenu.png]]
** Input DWI Volume: the DWI is loaded through the Volume module - it is th only mandatory input.
** Input ROI Volume (A/B): only 1 ROI is needed to achieve a tractography. If you want to evaluate the connection between two regions, you will give both ROIs.
** Input WM Volume: a white matter mask can be given as input to use ones provided by other tools or Slicer modules - it will supersede the brain mask even if enabled. Be mindful in setting a WM: tractography results can be impaired by a too restrictive WM.
** You are not obliged to set the ROIs or the white matter mask to smooth the DWI, create the brain mask and the tensor. These 3 steps just require a DWI.
* '''Smoothing panel:'''
[[Image:Smoothmenu.png]]
** Gaussian FWHM: this filter defines a Full Width Half Maximum. You can define it for each direction in modifying each component of the 3-vector.
** Advice: you can enable solely that functionality and compute several times with different parameters till you're satisfied with the output.
* '''Brain Mask panel:'''
[[Image:Maskmenu.png]]
** Lower/Higher Brain Threshold: this filter is based on a simple level set segmentation - intensities of the baseline lying between the two values will be represented, others are set to 0. This filter allows to remove ventricles from the tractography domain and most of the outside of the brain. This impacts positively the speed without impairing the tractography.
* '''Diffusion Tensor panel:'''
[[Image:Tensormenu.png]]
**Important: this step is not mandatory. It is here to evaluate the whole tensor and achieve measurements like FA, mode or trace. You did not need it to achieve tractography.
** FA, mode and trace are sent as scalar volumes and inserted in the MRML tree.
* '''Tractography panel:'''
[[Image:Tractomenu.png]]
** Total tracts: number of generated tracts per voxel
** Maximum tract length (mm): set the maximum length tracts could reach.
** Step size (mm): is the step length for the update vector
** Use spacing: must be used with caution - activate spacing to the update vector
** Stopping criteria: FA is used as the stopping criteria. Advice: as ROIs are defined in the grey matter FA are generally very low, therefore do not use generally.
* '''Connectivity Map panel:'''
[[Image:Connectmenu.png]]

== Development ==

===Dependencies===

Volumes

===Known bugs===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker.

===Usability issues===

Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker. Please select the '''usability issue category''' when browsing or contributing.

===Source code & documentation===

== More Information ==

===Acknowledgment===
National Alliance for Medical Image Computing (NAMIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149 (to Ron Kikinis, Marek Kubicki).

===References===
* [http://lmi.bwh.harvard.edu/papers/pdfs/2002/bjornemoMICCAI02.pdf Björnemo M, Brun A, Kikinis R, Westin CF. Regularized stochastic white matter tractography using diffusion tensor MRI. In Fifth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI'02). Tokyo, Japan, 2002;435-442.]
* [http://lmi.bwh.harvard.edu/papers/pdfs/2006/frimanTMI06.pdf Friman, O., Farneback, G., Westin CF. A Bayesian Approach for Stochastic White Matter Tractography. IEEE Transactions on Medical Imaging, Vol 25, No. 8, Aug. 2006]
* [http://www.na-mic.org/Wiki/index.php/Image:IC_posternew.png Shenton, M.E., Ngo, T., Rosenberger, G., Westin, C.F., Levitt, J.J., McCarley, R.W., Kubicki, M. Study of Thalamo-Cortical White Matter Fiber Tract Projections in Schizophrenia Using Diffusion Stochastic Tractography. Poster presented at the 46th Meeting of the American College of Neuropsychopharmacology, Boca Raton, FL, December 2007.]

Modules:StochasticTractography-Documentation-3.4

2009-04-15T23:24:29Z

Jvs:

Modules:StochasticTractography-Documentation-3.4

2009-04-15T23:22:03Z

Jvs:

Modules:StochasticTractography-Documentation-3.4

2009-04-15T20:01:15Z

Jvs:

Modules:StochasticTractography-Documentation-3.4

2009-04-15T19:55:09Z

Jvs:

Modules:StochasticTractography-Documentation-3.4

2009-04-15T19:51:25Z

Jvs:

Modules:StochasticTractography-Documentation-3.4

2009-04-15T19:50:05Z

Jvs:

Modules:StochasticTractography-Documentation-3.4

2009-04-15T19:48:01Z

Jvs:

Modules:StochasticTractography-Documentation-3.4

2009-04-15T19:46:28Z

Jvs:

Modules:StochasticTractography-Documentation-3.4

2009-04-15T19:45:13Z

Jvs:

Modules:StochasticTractography-Documentation-3.4

2009-04-15T19:41:34Z

Jvs:

Modules:StochasticTractography-Documentation-3.4

2009-04-15T19:37:33Z

Jvs:

Modules:StochasticTractography-Documentation-3.4

2009-04-15T19:36:50Z

Jvs:

Modules:StochasticTractography-Documentation-3.4

2009-04-15T19:35:36Z

Jvs:

Modules:StochasticTractography-Documentation-3.4

2009-04-15T19:33:21Z

Jvs:

Modules:StochasticTractography-Documentation-3.4

2009-04-15T19:32:28Z

Jvs:

Modules:StochasticTractography-Documentation-3.4

2009-04-15T19:30:53Z

Jvs:

Modules:StochasticTractography-Documentation-3.4

2009-04-15T19:29:29Z

Jvs:

Modules:StochasticTractography-Documentation-3.4

2009-04-15T19:26:30Z

Jvs:

Modules:StochasticTractography-Documentation-3.4

2009-04-15T19:23:19Z

Jvs:

Modules:StochasticTractography-Documentation-3.4

2009-04-15T19:18:37Z

Jvs:

Modules:StochasticTractography-Documentation-3.4

2009-04-15T19:17:54Z

Jvs:

Modules:StochasticTractography-Documentation-3.4

2009-04-15T19:16:50Z

Jvs:

Modules:StochasticTractography-Documentation-3.4

2009-04-15T19:16:02Z

Jvs:

Modules:StochasticTractography-Documentation-3.4

2009-04-15T19:15:34Z

Jvs:

Modules:StochasticTractography-Documentation-3.4

2009-04-15T19:06:54Z

Jvs:

Modules:StochasticTractography-Documentation-3.4

2009-04-15T19:04:35Z

Jvs:

Modules:StochasticTractography-Documentation-3.4

2009-04-15T19:02:49Z

Jvs:

Modules:StochasticTractography-Documentation-3.4

2009-04-15T19:00:16Z

Jvs:

File:General.png

2009-04-15T18:59:45Z

Jvs:

Modules:StochasticTractography-Documentation-3.4

2009-04-15T18:31:36Z

Jvs:

Modules:StochasticTractography-Documentation-3.4

2009-04-15T18:31:19Z

Jvs:

Modules:StochasticTractography-Documentation-3.4

2009-04-15T18:10:18Z

Jvs:

Modules:StochasticTractography-Documentation-3.4

2009-04-15T18:08:12Z

Jvs: