mriqc

Automated Quality Control and visual reports for Quality Assessment of structural (T1w, T2w) and functional MRI of the brain

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mriqc: image quality metrics for quality assessment of MRI

MRIQC is developed by the Poldrack Lab at Stanford University <https://poldracklab.stanford.edu> for use at the Center for Reproducible Neuroscience (CRN) <http://reproducibility.stanford.edu>, as well as for open-source software distribution.

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About

MRIQC extracts no-reference IQMs (image quality metrics) from structural (T1w and T2w) and functional MRI (magnetic resonance imaging) data.

MRIQC is an open-source project, developed under the following software engineering principles:

#. Modularity and integrability: MRIQC implements a nipype <http://nipype.readthedocs.io>_ workflow to integrate modular sub-workflows that rely upon third party software toolboxes such as FSL, ANTs and AFNI.

#. Minimal preprocessing: the MRIQC workflows should be as minimal as possible to estimate the IQMs on the original data or their minimally processed derivatives.

#. Interoperability and standards: MRIQC follows the the brain imaging data structure (BIDS) <http://bids.neuroimaging.io>, and it adopts the BIDS-App <http://bids-apps.neuroimaging.io> standard.

#. Reliability and robustness: the software undergoes frequent vetting sprints by testing its robustness against data variability (acquisition parameters, physiological differences, etc.) using images from OpenfMRI <https://openfmri.org>. Its reliability is permanently checked and maintained with CircleCI <https://circleci.com/gh/poldracklab/mriqc>.

MRIQC is part of the MRI image analysis and reproducibility platform offered by the CRN. This pipeline derives from, and is heavily influenced by, the PCP Quality Assessment Protocol <http://preprocessed-connectomes-project.github.io/quality-assessment-protocol>_.

Citation

.. topic:: When using MRIQC, please include the following citation:

Esteban O, Birman D, Schaer M, Koyejo OO, Poldrack RA, Gorgolewski KJ;
*MRIQC: Advancing the Automatic Prediction of Image Quality in MRI from Unseen Sites*;
PLOS ONE 12(9):e0184661; doi:`10.1371/journal.pone.0184661 <https://doi.org/10.1371/journal.pone.0184661>`_.

Support and communication

The documentation of this project is found here: http://mriqc.readthedocs.io/.

Users can get help using the mriqc-users google group <https://groups.google.com/forum/#!forum/mriqc-users>_.

All bugs, concerns and enhancement requests for this software can be submitted here: https://github.com/poldracklab/mriqc/issues.

Authors

Oscar Esteban, Krzysztof F. Gorgolewski. Poldrack Lab, Psychology Department, Stanford University, and Center for Reproducible Neuroscience, Stanford University.

.. topic:: Thanks

* The QAP developers (C. Craddock, S. Giavasis, D. Clark, Z. Shezhad, and J.
  Pellman) for the initial base of code which MRIQC was forked from.
* W Triplett and CA Moodie for their initial contributions with bugfixes and documentation, and
* J Varada for his contributions on the source code.

License information

We use the 3-clause BSD license; the full license is in the file LICENSE in the mriqc distribution.

All trademarks referenced herein are property of their respective holders.

Copyright (c) 2015-2017, the mriqc developers and the CRN. All rights reserved.

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