Journal article
Automated quality control for within and between studies diffusion MRI data using a non-parametric framework for movement and distortion correction
- Abstract:
- 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.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, pdf, 4.9MB, Terms of use)
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- Publisher copy:
- 10.1016/j.neuroimage.2018.09.073
Authors
+ National Institutes of Health
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- Funding agency for:
- Andersson, J
- Grant:
- 1U01AG052564-01
+ Wellcome Trust
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- Funding agency for:
- Alfaro-Almagro, F
- Andersson, J
- Grant:
- UK Biobank funding
- 1U01AG052564-01
- G1001354
+ Medical Research Council
More from this funder
- Funding agency for:
- Alfaro-Almagro, F
- Jbabdi, S
- Grant:
- UK Biobank funding
- MR/L009013/1
+ Engineering and Physical Sciences Research Council
More from this funder
- Funding agency for:
- Cottaar, M
- Sotiropoulos, S
- Grant:
- EP/L023067
- EP/L023067
+ Seventh Framework Programme
More from this funder
- Funding agency for:
- Bastiani, M
- Fitzgibbon, S
- Grant:
- 319456
- 319456
- Publisher:
- Elsevier
- Journal:
- NeuroImage More from this journal
- Volume:
- 184
- Pages:
- 801-812
- Publication date:
- 2018-09-26
- Acceptance date:
- 2018-09-25
- DOI:
- EISSN:
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1095-9572
- ISSN:
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1053-8119
- Pmid:
-
30267859
- Language:
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English
- Keywords:
- Pubs id:
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pubs:923587
- UUID:
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uuid:04a1d41e-b34c-4b26-a8bb-b05df0a2107b
- Local pid:
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pubs:923587
- Deposit date:
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2018-10-15
Terms of use
- Copyright holder:
- Bastiani et al
- Copyright date:
- 2018
- Notes:
- © 2018 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
- Licence:
- CC Attribution (CC BY)
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