Documentation/Nightly/Modules/DiffusionWeightedVolumeMasking

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Introduction and Acknowledgements

Title: Diffusion Brain Masking Author(s)/Contributor(s): Demian Wassermann, Isaiah Norton, Lauren O'Donnell (SPL, LMI, BWH, SlicerDMRI) License: 3D Slicer Contribution and Software License Agreement Acknowledgements: The SlicerDMRI developers gratefully acknowledge funding for this project provided by NIH NCI ITCR U01CA199459 (Open Source Diffusion MRI Technology For Brain Cancer Research), NIH P41EB015898 (National Center for Image-Guided Therapy) and NIH P41EB015902 (Neuroimaging Analysis Center), as well as the National Alliance for Medical Image Computing (NA-MIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149. Contact: <email>slicer-users@bwh.harvard.edu</email> Website: http://slicerdmri.github.io/

SlicerDMRI   Surgical Planning Laboratory   NAC   DWI   Brain mask

Module Description

Creates a brain mask from a diffusion weighted image volume. The mask can be used during diffusion tensor estimation or tractography seeding.

The brain mask is computed by averaging all baseline (non-diffusion-weighted) images, applying the Otsu thresholding algorithm to segment tissue voxels, and then removing small unconnected regions.

Use Cases

Most frequently used for these scenarios:

• Use Case 1: Create a brain mask from diffusion-weighted images (DWI). Use the brain mask to restrict tensor computation to the inside of the brain (remove noisy data outside the head). This makes a more attractive FA image.
• Use Case 2: Create a brain mask from diffusion-weighted images (DWI). Use the brain mask for seeding tractography.

Tutorials

Links to tutorials that use this module

• Slicer4 Diffusion Tensor Imaging Tutorial: https://www.slicer.org/slicerWiki/index.php/Documentation/Nightly/Training#Slicer4_Diffusion_Tensor_Imaging_Tutorial

Panels and their use

Parameters:

• IO: Input/output parameters
  • Input DWI Volume (inputVolume): Input DWI volume
  • Output Baseline Volume (outputBaseline): Extracted baseline volume
  • Output Diffusion Brain Mask (thresholdMask): Output Diffusion Brain Mask
• Mask Settings:
  • Baseline B-Value Threshold Parameter (baselineBValueThreshold): Volumes with B-value below this threshold will be considered baseline images and included in mask calculation.
  • Remove Islands in Brain Mask (removeIslands): Removes disconnected regions from brain mask.

List of parameters generated transforming this XML file using this XSL file. To update the URL of the XML file, edit this page.

Similar Modules

• DWIToDTIEstimation

References

• http://slicerdmri.github.io/
• Otsu thresholding method: https://en.wikipedia.org/wiki/Otsu%27s_method

Information for Developers

• https://github.com/SlicerDMRI