A Semi-Automatic Method for Segmentation of the Coronary Artery Tree from Angiography

Nowadays, medical diagnostics using images has a considerable importance in many areas of medicine. It promotes and makes easier the acquisition, transmission and analysis of medical images. The use of digital images for diseases evaluations or diagnostics is still growing up and new application modalities are always appearing. This paper presents a methodology for a semi-automatic segmentation of the coronary artery tree in 2D X-Ray angiographies. It combines a region growing algorithm and a differential geometry approach. The proposed segmentation method identifies about 90% of the main coronary artery tree.