Quality assurance measures automatically extracted from acquired MR images (e.g. noise analysis, motion params and outlier detection).
Benefit Hypothesis
If quality assurance measures can be automatically extracted from MR images and displayed in the XNAT UI in a convenient manner, then it will be much easier for researchers to detect problems with their sequence design/scanner faults, and hopefully this occurs at an earlier point when it is possible to correct the problem (rather than after the study has already finished).
Acceptance Criteria
[ ] all major MR contrasts have a QA sequence
[ ] QA detects ~80% of problems with acquired images
github-actions[bot]
commented
1 year ago
Description
Quality assurance measures automatically extracted from acquired MR images (e.g. noise analysis, motion params and outlier detection).
Benefit Hypothesis
If quality assurance measures can be automatically extracted from MR images and displayed in the XNAT UI in a convenient manner, then it will be much easier for researchers to detect problems with their sequence design/scanner faults, and hopefully this occurs at an earlier point when it is possible to correct the problem (rather than after the study has already finished).
Acceptance Criteria
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