Difference between revisions of "Modules:ROISeeding-Documentation-3.4"

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|[[Image:screenshotBlank.png|thumb|280px|Caption 1]]
 
|[[Image:screenshotBlank.png|thumb|280px|Caption 1]]
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===Module Type & Category===
 
===Module Type & Category===
  
Type: Interactive or CLI
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Type: CLI
  
 
Category: Base or (Filtering, Registration, ''etc.'')
 
Category: Base or (Filtering, Registration, ''etc.'')
  
 
===Authors, Collaborators & Contact===
 
===Authors, Collaborators & Contact===
* Author1: Affiliation & logo, if desired
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* Author1: Raul San Jose, BWH
* Contributor1: Affiliation & logo, if desired
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* Contributor1: Alex Yarmakovich, Isomics
* Contributor2: Affiliation & logo, if desired
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* Contact: Raul San Jose, lmi.bwh.harvard.edu/~rjosest
* Contact: name, email
 
  
 
===Module Description===
 
===Module Description===
Overview of what the module does goes here.
+
ROI Seeding is a tractography implementation that allows a user to seed tracts from a region of interest (ROI). The ROI is defined as a labelmap and has to be provided by the user. One approach to generate the ROI is by means of the Editor module.
  
 
== Usage ==
 
== Usage ==
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===Examples, Use Cases & Tutorials===
 
===Examples, Use Cases & Tutorials===
  
* Note use cases for which this module is especially appropriate, and/or link to examples.
+
* We want to study the white matter integrate across a population for a given tract. ROISeeding can be used to carry this study. First, a region of interest in the tract that is under study has to be defined, for example by manually delineating the ROI using the Editor module. Second, the DWI has to be loaded and the tensor has to be created using the [Diffusion Tensor Estimation | Modules:DiffusionTensorEstimation-Documentation-3.4]. Thrid, start the ROI Seeding using the DTI volume and the ROI labelmap as main volume inputs.
* Link to examples of the module's use
 
* Link to any existing tutorials
 
  
 
===Quick Tour of Features and Use===
 
===Quick Tour of Features and Use===
List all the panels in your interface, their features, what they mean, and how to use them. For instance:
+
The module is very straighforward to use:
  
* '''Input panel:'''
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* '''Input DTI volume:'''set the DTI volume that is going to be used for tractography
 
* '''Parameters panel:'''
 
* '''Parameters panel:'''
 
* '''Output panel:'''
 
* '''Output panel:'''
 
* '''Viewing panel:'''
 
* '''Viewing panel:'''
  
 
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=== Caveats and other limitations ===
Should note somewhere that ROISeeding module does not work when the labelmap dimensions do not match the DTI volume dimensions. The work-around is to resample labelmap using Filtering -> Resample Volume 2. But this is not immediately obvious.. -inorton
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ROISeeding module does not work when the labelmap dimensions do not match the DTI volume dimensions. The work-around is to resample labelmap using [Filtering -> Resample Volume 2 | http://www.slicer.org/slicerWiki/index.php/Modules:ResampleVolume2-Documentation-3.4].
  
 
== Development ==
 
== Development ==
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===Dependencies===
 
===Dependencies===
  
Other modules or packages that are required for this module's use.
+
None
  
 
===Known bugs===
 
===Known bugs===
  
 
Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker.  
 
Follow this [http://na-mic.org/Mantis/main_page.php link] to the Slicer3 bug tracker.  
 
  
  

Revision as of 13:50, 17 March 2009

Home < Modules:ROISeeding-Documentation-3.4

Return to Slicer 3.4 Documentation

Module Name

MyModule

Caption 1

General Information

Module Type & Category

Type: CLI

Category: Base or (Filtering, Registration, etc.)

Authors, Collaborators & Contact

  • Author1: Raul San Jose, BWH
  • Contributor1: Alex Yarmakovich, Isomics
  • Contact: Raul San Jose, lmi.bwh.harvard.edu/~rjosest

Module Description

ROI Seeding is a tractography implementation that allows a user to seed tracts from a region of interest (ROI). The ROI is defined as a labelmap and has to be provided by the user. One approach to generate the ROI is by means of the Editor module.

Usage

Examples, Use Cases & Tutorials

  • We want to study the white matter integrate across a population for a given tract. ROISeeding can be used to carry this study. First, a region of interest in the tract that is under study has to be defined, for example by manually delineating the ROI using the Editor module. Second, the DWI has to be loaded and the tensor has to be created using the [Diffusion Tensor Estimation | Modules:DiffusionTensorEstimation-Documentation-3.4]. Thrid, start the ROI Seeding using the DTI volume and the ROI labelmap as main volume inputs.

Quick Tour of Features and Use

The module is very straighforward to use:

  • Input DTI volume:set the DTI volume that is going to be used for tractography
  • Parameters panel:
  • Output panel:
  • Viewing panel:

Caveats and other limitations

ROISeeding module does not work when the labelmap dimensions do not match the DTI volume dimensions. The work-around is to resample labelmap using [Filtering -> Resample Volume 2 | http://www.slicer.org/slicerWiki/index.php/Modules:ResampleVolume2-Documentation-3.4].

Development

Dependencies

None

Known bugs

Follow this link to the Slicer3 bug tracker.


Usability issues

Follow this link to the Slicer3 bug tracker. Please select the usability issue category when browsing or contributing.

Source code & documentation

Customize following links for your module.

Links to documentation generated by doxygen.


More Information

Acknowledgment

Include funding and other support here.

References

Publications related to this module go here. Links to pdfs would be useful.