bioRxivBioinformaticsPreprint
MRIQC Web-API: Crowdsourcing image quality metrics and expert quality ratings of structural and functional MRI
Oscar EstébaniD, Ross Blair, Dylan M. NielsoniD, JC. Varada, Sean MarrettiD, Adam G. ThomasiD, Russell Alan PoldrackiD, Krzysztof J. GorgolewskiiD
Abstract
SynopsisThe MRIQC Web-API is a resource for scientists to train new automatic quality classifiers. The MRIQC Web-API has collected more than 30K sets of image quality measures automatically extracted from BOLD and T1-weighted scans using MRIQC. MRIQC is an automated MRI Quality Control tool, and here we present an extension to crowdsource these quality metrics along with anonymized metadata and manual quality ratings. This new resource will allow a better understanding of the normative values and distributions of these quality metrics, help determine the relationships between image quality and metadata such as acquisition parameters and finally, provide a cost-effective, easy way to annotate the quality of a large number of cross-site MR scans.
- assay: imaging
- research focus: benchmarking
- research focus: database / resource
- approach: experimental assay
- Citations
- 4
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