Heart Outer Surface Segmentation from Computed Tomography Images

Volumetric heart segmentation is an essential operation in cardiology; it makes it possible to locate the cardiac lesions, quantify them, and follow their evolution for treatment. From the study of heart outer surface segmentation, several characteristics can be extrapolated and interpreted as coronary arteries calcifications (CAC) lesions. Image segmentation is the appropriate tool for such localization. In this work, we have realized an automatic system, which segments, the heart outer surface using only native computer tomography acquisitions (CCT). A multi-level threshold, mathematical morphology, and 3D connected component labeling are performed for this purpose. In the end, the 3D view is realized. We used 32 patients from the OrCascore dataset. We compared our segmentation with ground truth volumes, plotted by two experienced cardiologists. Our approach achieved an accuracy, F1score, DICE, and a JACCARD coefficient of 96.99%, 92.01%, 91.81%, and 85.23% respectively in a short computation time.