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

• want to study fiber paths from a single region of interest (ROI)
• 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 with standard measures like fractional anisotropy (FA), mode and trace, 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 A to region B and B to A ROI filtering ROI filtering from A to B ROI filtering from B to A

• link tutorial

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:

• Smoothing panel:

• Brain Mask panel:

• Diffusion Tensor panel:

• Tractography panel:

• Connectivity Map panel:

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.

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

• 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.
• 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
• 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.