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WhiteMatterAnalysis (WMA) provides fiber clustering and tractography analysis tools.

WMA Installation and Usage

1. Install Python 3:

Miniconda is a nice option because it includes pip, setuptools, and all library dependencies (such as VTK and scipy).

2. Install whitematteranalysis with pip:

The following command will use pip to install whitematteranalysis from this source repository and all library dependencies:

$ pip install git+https://github.com/SlicerDMRI/whitematteranalysis.git

Note: On macOS, to be able to use pip, X-code needs to be installed using $ xcode-select --install.

Run $ wm_quality_control_tractography.py --help to test if the installation is successful.

3. Documentation

The whitematteranalysis package documentation can be found at https://whitematteranalysis.readthedocs.io/en/latest/.

$ wm_apply_ORG_atlas_to_subject.sh \
  -i input_tractography.vtk \
  -o output_dir \
  -a path_to_atlas/ORG-Atlases-v1.x \
  -s /Applications/Slicer5.2.2.app/Contents/MacOS/Slicer \
  -d 1 \
  -m /Applications/Slicer5.2.2.app/Contents/Extensions-31382/SlicerDMRI/lib/Slicer-5.2/cli-modules/FiberTractMeasurements


Please cite the following papers for using the code and/or the training data :

Zhang, F., Wu, Y., Norton, I., Rathi, Y., Makris, N., O'Donnell, LJ. 
An anatomically curated fiber clustering white matter atlas for consistent white matter tract parcellation across the lifespan. 
NeuroImage, 2018 (179): 429-447

O'Donnell LJ, Wells III WM, Golby AJ, Westin CF. 
Unbiased groupwise registration of white matter tractography.
In MICCAI, 2012, pp. 123-130.

O'Donnell, LJ., and Westin, CF. Automatic tractography segmentation
using a high-dimensional white matter atlas. Medical Imaging,
IEEE Transactions on 26.11 (2007): 1562-1575.

For projects using Slicer and SlicerDMRI please also include the following text (or similar) and citations: