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 between two regions of the Grey Matter of the brain using ROIs (Region Of Interest) as inputs. 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

Examples, Use Cases & Tutorials

The stochastic tractography module interface implements a real workflow with the following steps:

Stochastic tractography panel
  • Step1 : smooth with a Half Width Full Maximum filter,
Smoothing step
Brain mask step
  • Step2 : generate step a brain mask,
Tensor step
Tensor step: FA
  • Step3 : create a DTI (Diffusion Tensor Image) tensor with standard measures like fractional anisotropy (FA), mode and trace,
Tensor step: mode
Tensor step: trace
  • Step4 : run tractography and build connection maps.
Union of A to B and B to A
Intersection of A to 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