Maximum a posteriori estimation method for aorta localization and coronary seed identification

A robust method is proposed for the automatic identification of seed points (coronary ostia) for the segmentation of coronary arteries from CT image.Our method provides both aorta and ostia localization.Anatomical and geometrical priors are statistically obtained and used in MAP estimation.Two components are jointly found in MAP estimation (e.g. ascending and descending aortas, left and right coronary ostia). We propose a robust method for the automatic identification of seed points for the segmentation of coronary arteries from coronary computed tomography angiography (CCTA). The detection of the aorta and the two ostia for use as seed points is required for the automatic segmentation of coronary arteries. Our method is based on a Bayesian framework combining anatomical and geometrical features. We demonstrate the robustness and accuracy of our method by comparison with two conventional methods on 130 CT cases.