pyfMRIqc: A Software Package for Raw fMRI Data Quality Assurance

Abstract

pyfMRIqc is a tool for checking the quality of raw functional magnetic resonance imaging (fMRI) data. pyfMRIqc produces a range of output files which can be used to identify fMRI data quality issues such as artefacts, motion, signal loss etc. This tool creates a number of 3D and 4D NIFTI files that can be used for in depth quality assurance. Additionally, 2D images are created for each NIFTI file for a quick overview. These images and other information (e.g. about signal-to-noise ratio, scan parameters, etc.) are combined in a user-friendly HTML output file. pyfMRIqc is written entirely in Python and is available under a GNU GPL3 license on GitHub (https://drmichaellindner.github.io/pyfMRIqc/). pyfMRIqc can be used from the command line and therefore can be included as part of a processing pipeline or used to quality-check a series of datasets using batch scripting. The quality assurance of a single dataset can also be performed via dialog boxes. Funding statement: Brendan Williams is funded by the Magdalen Vernon PhD Studentship of the School of Psychology and Clinical Language Sciences, University of Reading. The project was funded by the Centre for Integrative Neuroscience and Neurodynamics, and the University of Reading.

Keywords

• neuroscience
• neuroimaging
• fmri
• python
• quality control
• artefacts