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Automated quality control for within and between studies diffusion MRI data using a non-parametric framework for movement and distortion correction

Bastiani, Matteo; Cottaar, Michiel; Fitzgibbon, Sean P.; Suri, Sana; Alfaro-Almagro, Fidel; Sotiropoulos, Stamatios N.; Jbabdi, Saad; Andersson, Jesper


Matteo Bastiani

Michiel Cottaar

Sean P. Fitzgibbon

Sana Suri

Fidel Alfaro-Almagro

Stamatios N. Sotiropoulos

Saad Jbabdi

Jesper Andersson


Diffusion MRI data can be affected by hardware and subject-related artefacts that can adversely affect downstream analyses. Therefore, automated quality control (QC) is of great importance, especially in large population studies where visual QC is not practical. In this work, we introduce an automated diffusion MRI QC framework for single subject and group studies. The QC is based on a comprehensive, non-parametric approach for movement and distortion correction: FSL EDDY, which allows us to extract a rich set of QC metrics that are both sensitive and specific to different types of artefacts. Two different tools are presented: QUAD (QUality Assessment for DMRI), for single subject QC and SQUAD (Study-wise QUality Assessment for DMRI), which is designed to enable group QC and facilitate cross- studies harmonisation efforts.

Journal Article Type Article
Publication Date Jan 1, 2019
Print ISSN 1053-8119
Electronic ISSN 1095-9572
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 184
Pages 801-812
Keywords Diffusion MRI ; Quality control ; Movement ; Susceptibility ; Eddy current
Publisher URL


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