Fully automatic 3D segmentation of coronary arteries based on mathematical morphology
In this paper we propose a fully automatic algorithm for coronary artery extraction from X-ray data (3D-CT scan, 64 detectors) based on the mathematical morphology techniques and guided by anatomical knowledge. Growing and thresholding methods, in their most general form, are not sufficient to extract only the whole coronary arteries, because of the properties of these images. Finding appropriate methods is known to be a challenging problem because of the data imperfections such as noise, heterogeneous intensity and contrasts of similar tissues. We deal with these challenges by employing discrete geometric tools to fit on the arteries form independently from any perturbation of the data.