Pujol S, Gollub R

-1-National Alliance for Medical Image Computing

StochasticTractography

Module

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Slicer3 Training Compendium

Pujol S, Gollub R

-2-National Alliance for Medical Image Computing

Introduction

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•The stochastic tractography filter extracts nerve fiber bundles from DWI images. Unlike streamline tractography, stochastic tractography uses a probabilistic framework to perform tractography.

•By incorporating uncertainty due to fiber crossings, imaging noise and resolution, stochastic tractography can robustly extract fiber bundles when streamline tractography cannot.

•The tracts generated by the stochastic tractography filter can be used to generate a connectivity probability image, which can be used to study connectivity between different regions of the brain.

Pujol S, Gollub R

-3-National Alliance for Medical Image Computing

Materials and Req.’s

This course requires the installation of the Slicer3 softwareand training dataset accessible at the following locations:

• Slicer 3 Softwarehttp://www.na-mic.org/Wiki/index.php/Slicer:Slicer3

• Training Dataset (packaged and compressed)http://www.na-mic.org/Wiki/images/0/01/IJdata.tar.gz

• Prerequisite Skills– Loading images into Slicer 3

DisclaimerIt is the responsibility of the user of 3DSlicer tocomply with both the terms of the license and withthe applicable laws, regulations and rules.

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Pujol S, Gollub R

-4-National Alliance for Medical Image Computing

Data

This course is built upon three datasets of a single

healthy subject brain:

DWI (Nrrd) Whitematter Image (Nrrd)

ROI Image (Nrrd)

shown overlaid on baseline DWI, tan pixel is seed ROI

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Pujol S, Gollub R

-5-National Alliance for Medical Image Computing

ROI Image

Regions of Interest (ROI) denoted by an integer label.

Optionally, other regions can be specified to filter the tracts

An ROI image overlaid on FA image, regions with zero label are transparent. The ROI image is an integer image. Each value defines a unique region.

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Pujol S, Gollub R

-6-National Alliance for Medical Image Computing

Learning objective

Following this tutorial, you’ll be able to extract nerve fiber bundles and compute a connectivity map using the stochastic tractography module.

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Stochastic TractographyModule

Generate Connectivity Map

DWI,White Matter,ROI Images

ConnectivityMap

Pujol S, Gollub R

-7-National Alliance for Medical Image Computing

Loading Volumes1. Obtain the tutorial data and

uncompress it.

2. Use Slicer3 to load in

1.namic01-dwi_compressed.nhdr

2.namic01-ROI-leftcingulum.nhdr

3.namic01_dwi_compressed_WMMask.nhdr

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Pujol S, Gollub R

-8-National Alliance for Medical Image Computing

Open stochastic tractography module through the “Modules” drop down menu.

Open ST Filter Module

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Tractography -> Stochastic -> Stochastic Tractography Filter

Pujol S, Gollub R

-9-National Alliance for Medical Image Computing

ST Filter Parameters• Copy the parameters

in the image.

• The seed point is 2 because that the label in the ROI image of the region we wish to start the tractography.

• The maximum tract length is 400. We don’t want to restrict the length of the tract in this case so we set it to a large number.

• The remaining options can be left at their default values. Press apply to start the filter.

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Hint: To learn more about any option, hover over it with the mouse.

Pujol S, Gollub R

-10-National Alliance for Medical Image Computing

Generate Connectivity Map

•Open Generate Connectivity Map module using the “Modules” drop down menu.

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Tractography -> Stochastic -> Generate Connectivity Map

Pujol S, Gollub R

-11-National Alliance for Medical Image Computing

GCMap Parameters 1. Copy the parameter

settings shown in the image.

2. Input tracts: Locate the filename of the tracts generated using the stochastic tractography module.

3. Input Volume: This is the dwi image used to generate the tracts.

4. Output Volume: Tell Slicer3 to create a new output volume.

5. Click apply button.

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Hint: To learn more about any option, hover over it with the mouse.

Pujol S, Gollub R

-12-National Alliance for Medical Image Computing

CMap Visualization•The generated connectivity image is called: “Generate Connectivity Map Volume1”

•The connectivity map is a floating point image where every voxel’s value is equal to the probability that that voxel is connected to the seed region via a fiber tract.

•You can use the “VolumeRendering” module to more easily visualize the data.

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Pujol S, Gollub R

-13-National Alliance for Medical Image Computing

Acknowledgments

• We would like to acknowledge the support from the following NIH grants: P41 RR13218, R01 MH074794, and U54 EB005149 (National Alliance for Medical Image Computing, NA-MIC).

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