Study of CT Image Segmentation Based on CV Model

The medical image has the characteristics of blurred edges and heterogeneity, it is difficult to achieve the goal of segmentation using the traditional Chan-Vese model method, at the same time, the method is large amount of calculation and the speed is slow. Therefore, this paper presents an improved segmentation algorithm based on the Chan-Vese model, the convergence speed of the level set and the effectiveness of energy item are enhanced according to the current active contour and the local information of image during the iterative process, and a new segmentation method for image sequence is proposed. The experiments show that the improved Chan-Vese model can extract the object interested in the image quickly and exactly, it is an ideal method for medical image segmentation.