Abstract
Contact for queries: luca.biasiolli@cardiov.ox.ac.uk or s.e.petersen@qmul.ac.uk
UK Biobank: Automated aortic lumen segmentation results
Aortic distensibility can be calculated using semi-automated methods to segment the aortic lumen on cine CMR (Cardiovascular Magnetic Resonance) images. However, these methods require visual quality control and manual localization of the region of interest (ROI) of ascending (AA) and proximal descending (PDA) aorta, which limit the analysis in largescale population-based studies. Using 5,100 scans from UK Biobank, this study sought to develop and validate a fully automated method to
1) detect and locate the ROIs of AA and PDA, and
2) provide a quality control mechanism.
The proposed method for automated AA and PDA localization was extremely accurate and the automatically derived detection probabilities provided a robust mechanism to detect low quality scans for further human review. Applying the proposed localization and quality control techniques promises at least a ten-fold reduction in human involvement without sacrificing any accuracy.
Please note that this return contains data for the second tranche of results returned by application 2964. Further data are available from return
1866