Atherosclerotic blood vessel tracking and lumen segmentation in topology changes situations of MR image sequences

Carotid artery vessel tracking and lumen segmentation is an important task for atherosclerotic plaque study, where the active contour model Snake has become one of the most powerful techniques for this purpose. However, its intrinsic weakness in initialization and topology changes handling limits its application in complicated situations. In this research, we focus our work on atherosclerotic blood vessel tracking and lumen contour segmentation of magnetic resource (MR) image sequences, along which the blood vessel bifurcates at indefinite position. To automatically capture this topology change in the processing, a practical solution is proposed by extending our previous research work. The procedure first presegments each MR slice into regions, and then uses a decision tree to track the blood vessel´s topology change. Finally, the minimal path Snake (MPS) algorithm is applied to further search optimal lumen contours. Some experimental results in the preliminary study are provided to demonstrate its encouraging performance