MRIQC specifications

Information


Unique identifier OMICS_15470
Name MRIQC
Software type Package/Module
Interface Command line interface, Application programming interface
Restrictions to use None
Operating system Unix/Linux
Programming languages Python
License BSD 3-clause “New” or “Revised” License
Computer skills Advanced
Version 0.9.5
Stability Stable
Requirements
Numpy, nipype
Source code URL https://codeload.github.com/poldracklab/mriqc/legacy.tar.gz/master
Maintained Yes

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Documentation


Maintainer


  • person_outline Oscar Esteban <>

Publication for MRIQC

MRIQC in publications

 (2)
PMCID: 5770339
PMID: 29079522
DOI: 10.1016/j.neuroimage.2017.10.034

[…] unified platform for quality control that attempts to incorporate different qc pipelines and their associated metrics. the qc tools to come out of our work are designed to be easily integrated into mriqc (, ), a project affiliated to pcpqap., due to the uncertainty about the suitability of the qc metrics discussed above to successfully assess image quality objectively and to detect the majority […]

PMCID: 5139672
PMID: 27922632
DOI: 10.1038/sdata.2016.110

[…] included with the data set as reference material., after processing the source data, bold contrast (fmri) and t1-weighted anatomical imaging data were processed by the mri quality control protocol (mriqc https://github.com/poldracklab/mriqc). mriqc computes several quality control metrics available in the published literature., all t1-weighted images were skull-stripped [afni 3dskullstrip], […]

MRIQC institution(s)
Department of Psychology, Stanford University, CA, USA; Data Science and Sharing Team, National Institute of Mental Health, Bethesda, MD, USA; Functional MRI Facility, National Institute of Mental Health, Bethesda, MD, USA
MRIQC funding source(s)
Supported by the Laura and John Arnold Foundation.

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