WhiteMatterAnalysis (WMA) provides fiber clustering and tractography analysis tools.
Miniconda is a nice option becuase it includes pip, setuptools, and all library dependencies (such as VTK and scipy).
- Download and install Miniconda (Python 3.7) from https://conda.io/miniconda.html
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 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.
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Please see the following page for instructions of applying a pre-provided anatomically curated white matter atlas, along with the computation tools provided in whitematteranalysis, to perform subject-specific tractography parcellation.
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WMA implements algorithms from publications listed here: http://projects.iq.harvard.edu/whitematteranalysis/publications
Please cite the following papers:
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.
O'Donnell LJ, Wells III WM, Golby AJ, Westin CF.
Unbiased groupwise registration of white matter tractography.
In MICCAI, 2012, pp. 123-130.
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
For projects using Slicer and SlicerDMRI please also include the following text (or similar) and citations:
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How to cite the Slicer platform
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An example of how to cite SlicerDMRI (modify the first part of the sentence according to your use case):
"We performed diffusion MRI tractography and/or analysis and/or visualization in 3D Slicer (www.slicer.org) via the SlicerDMRI project (dmri.slicer.org) (Norton et al. 2017)."