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Short Description
Calculate parameters of the Sparse Fascicle Model on diffusion MRI data.
Full Description

dipy-sfm

This container calculates SFM parameters [Rokem2015]_, based on diffusion MRI
data.

.. [Rokem2015] Ariel Rokem, Jason D. Yeatman, Franco Pestilli, Kendrick
N. Kay, Aviv Mezer, Stefan van der Walt, Brian A. Wandell
(2015). Evaluating the accuracy of diffusion MRI models in white
matter. PLoS ONE 10(4): e0123272. doi:10.1371/journal.pone.0123272

Parameters

fdata : str

The name of a nifti file with preprocessed diffusion data.

fbval : str

The name of a text-file with b-values in FSL format.

fbvec : str

The name of a text file with the b-vectors in FSL format.

fmask : str, optional

The name of a nifti file containing boolean mask of locations to
analyze. Default: no masking

Metadata

The mounted input folder should contain a metadata.json file with the following
format:

{
"fdata":"HARDI150.nii.gz",
"fbval":"HARDI150.bval",
"fbvec":"HARDI150.bvec",
"fmask":"mask.nii.gz"
}

Where fmask parameter is optional.

Returns

root_sfm.nii.gz : file
A nifti file containing the 362 SFM parameters.

root_{fa, di}: files
Nifti files containing the Fiber Anisotrpopy (FA), and Dispersion Index (DI).

Examples

To run this container use:

docker run --rm -it -v /path/to/data:/input -v /path/to/output/:/output arokem/dipy-sfm

Where the folder /path/to/data/ should contain the metadata.json file,

Notes

This uses the dipy.reconst.sfm module: http://nipy.org/dipy/reference/dipy.reconst.html#module-dipy.reconst.sfm

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arokem
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