Segmentation and tracking of the coronary arteries

In most developed countries, heart disease is the leading cause of death. As a result of plaque buildup, the heart\u27s normal beating motion is disrupted. The detection of this irregular behavior is the motivation behind the computer vision system proposed in this paper. This research aims to provide a foundation for future work relating to hear motion, pathologic evaluation, and 3-D reconstruction. This system uses a two-step process to analyze coronary artery motion over a sequence of frames. First, the vessel skeletons are extracted in each image by looking for regions of low gradient magnitude. A vessel hierarchy is built to identify each unique branch of the coronary tree. Then, a motion trajectory is computed for each point of the segmented artery network. The correspondence algorithm used is capable of handling conclusion. To minimize computational complexity, the point correspondence method operates on each tree branch independently. The output of this system is a set of vectors which describe the general motion of each coronary branch