Extracting coronary artery is one of the vital steps in the analysis process based on the modality of computed tomography angiography (CTA), the aim of which is to recognize coronary artery from 3D volume data, and then provide evidences of analysis and quantitative measurement information for coronary artery computer aided detection.
According to the structure features of coronary artery angiography scanned by multiple slices computed tomography (MSCT), an automatic segmentation algorithm is proposed. Firstly, detect and recognize the multiple seed points of the coronary artery in the scale space automatically from the 3D complex cardiac image datasets. Secondly, an improved layer region growing algorithm oriented to 3D tubular structure tissues is proposed to segment the coronary artery.
Experiments show that the algorithm can extract coronary artery vessels effectively, which can improve the automation of coronary artery analysis, thus improve physicians' work efficiency.