Automated left ventricular myocardium segmentation using 3D deeply supervised attention U‐net for coronary computed tomography angiography; CT myocardium segmentation

Abstract

We developed a novel deep learning-based approach for the automated segmentation of the LVM on CCTA images. We demonstrated the high accuracy of the proposed learning-based segmentation method through comparison with ground truth contour of 100 clinical patient cases using six quantitative metrics. These results show the potential of using automated LVM segmentation for computer-aided delineation of CADs in the clinical setting.