Abstract
To present a novel fully automated method for assessing the quality of magnetic resonance imaging (MRI) data acquired in a clinical trials environment. This work was performed in the context of clinical trials for multiple sclerosis. Quality control (QC) procedures included were: (i) patient brain identity verification, (ii) alphanumeric parameter matching, (iii) signal-to-noise ratio estimation, (iv) gadolinium-enhancement verification, and (v) detection of ghosting due to head motion. Each QC procedure produces a quantitative measurement which is compared against an acceptance threshold that was determined based on receiver operating characteristic analysis of traditional manual and visual QC performed by trained experts. The automated QC results have high sensitivity and specificity when compared with the visual QC. Our automated objective QC procedure can replace many manual subjective procedures to provide increased data throughput while reducing reader variability.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
