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

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* You want to study fiber path from a single region of interest (ROI)
 
* You want to study fiber path from a single region of interest (ROI)
 
* You want to evaluate connectivity between two ROIs
 
* You want to evaluate connectivity between two ROIs
 
  
 
=== Description ===
 
=== Description ===
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With the stochastic tractography module, you can:  
 
With the stochastic tractography module, you can:  
 
 
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{|
 
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* Feature 6 : produce connection maps in case 2 ROIs are given with ROI filtering
 
* Feature 6 : produce connection maps in case 2 ROIs are given with ROI filtering
** showing only tracts connecting A to region B and B to A
+
** showing only tracts connecting region A to region B and B to A
 
{|
 
{|
 
|[[Image:connectAB2.png|thumb|500px|ROI filtering]]
 
|[[Image:connectAB2.png|thumb|500px|ROI filtering]]
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* [http://www.na-mic.org/Wiki/index.php/Python_Stochastic_Tractography_Tutorial link tutorial]
 
* [http://www.na-mic.org/Wiki/index.php/Python_Stochastic_Tractography_Tutorial link tutorial]
 
 
===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:
 
List all the panels in your interface, their features, what they mean, and how to use them. For instance:
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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 20:01, 15 April 2009

Home < Modules:StochasticTractography-Documentation-3.4
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Module Name

Stochastic Tractography

Corpus callosum with stochastic tractography
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 in the White Matter between two regions of interest (ROIs) of the Grey Matter of the brain. These ROIs define grey matter regions ensuring a specific neurophysiological function. Extensively, study involving more than two regions could still be done by pairing the regions two by two and computing them separetely to finally gather the results.

Usage

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

Description

Stochastic tractography panel

With the stochastic tractography module, you can:

  • Feature 1 : smooth using a Half Width Full Maximum gaussian filter
Smoothing step
  • Feature 2 : generate a brain mask
Brain mask step
  • Feature 3 : create a DTI (Diffusion Tensor Image) tensor
Tensor step
  • Feature 4 : produce different measures based on the tensor like fractional anistropy (FA), mode and trace
Tensor step: FA
Tensor step: mode
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
Union of A to B and B to A
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
ROI filtering
ROI filtering from A to B
ROI filtering from B to A

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:

  • IO panel:

IOmenu.png

  • Smoothing panel:

Smoothmenu.png

  • Brain Mask panel:

Maskmenu.png

  • Diffusion Tensor panel:

Tensormenu.png

  • Tractography panel:

Tractomenu.png

  • Connectivity Map panel:

Connectmenu.png

Development

Dependencies

Volumes

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

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