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sMRIPrep is a structural magnetic resonance imaging (sMRI) data
preprocessing pipeline that is designed to provide an easily accessible,
state-of-the-art interface that is robust to variations in scan acquisition
protocols and that requires minimal user input, while providing easily
interpretable and comprehensive error and output reporting.
It performs basic processing steps (subject-wise averaging, B1 field correction,
spatial normalization, segmentation, skullstripping etc.) providing
outputs that can be easily connected to subsequent tools such as
fMRIPrep <https://github.com/nipreps/fmriprep>
or
dMRIPrep <https://github.com/nipreps/dmriprep>
.
The workflow is based on Nipype <https://nipype.readthedocs.io>
and encompasses
a combination of tools from well-known software packages, including
FSL <https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/>
,
ANTs <https://stnava.github.io/ANTs/>
,
FreeSurfer <https://surfer.nmr.mgh.harvard.edu/>
,
and Connectome Workbench <https://humanconnectome.org/software/connectome-workbench>
__.
More information and documentation can be found at
https://www.nipreps.org/smriprep/.
Support is provided on neurostars.org <https://neurostars.org/tags/smriprep>
_.
sMRIPrep is built around three principles:
Please acknowledge this work by mentioning explicitly the name of this software
(sMRIPrep) and the version, along with a link to the GitHub repository <https://github.com/nipreps/smriprep>
or the Zenodo reference
(doi:10.5281/zenodo.2650521 <https://doi.org/10.5281/zenodo.2650521>
).