Medical Image Segmentation Based on Level Sets Method
Qing Zhang · Beijing shengwu yixue gongcheng · 2006
Segmentation of structure in medical images is an important research topic.It is used in patient diagnose,image-guided surgery,and medical data visulization.One common approach to solve this problem is to segment objects of interest with active contours or snake.Two active contour models,one based on an edge-stopping function,while the other is an energy minimization algorithm,are demonstrated.Both methods can be put into a level-set framework using a Lipschitz function for automatic topology changes.The experiments show that the first method can only detect object defined by a strong gradient,while the second method does not have this constraint.