A hybrid algorithm for automatic heart segmentation in ct angiography
In this work, we present a hybrid algorithm to automatically delineate the heart volume in 3D cardiac computed tomography (CT) datasets for the visualization of coronary arteries. Our work eliminates the tedious and time consuming step of manually removing obscuring structures around the heart (ribs, sternum, liver...). It quickly provides a clear and well defined view of the coronaries. So far, works related to heart segmentation have mainly focused on heart cavities delineation, which is not suited for coronaries visualization. In contrast, our algorithm extracts the heart cavities, the myocardium and coronaries as a single object. The proposed approach is based on the fitting of a geometric model of the heart to a set of automatically extracted 3D points lying on the heart shell. A novel two-stage fitting scheme is used to improve the robustness to the outliers. The fitting result is further refined using a Random Walker (RW) segmentation approach. Qualitative analysis of results obtained on a 70 exam database shows the efficiency and the accuracy of our approach.