Hybrid Mumford-Shah Model for Medical Image Segmentation Based on Gradient
Yuqing Song · Jisuanji gongcheng · 2007
The proposed level set method by C-V is failed to control the local feature.In order to eliminate C-V method’s demerits,a hybrid Mumford-Shah model based on gradient(HMSG) is proposed.HMSG model has the merits of the geometric active contour based on edge and C-V method based on region.In addition,a rule of parameter choice is given to harmonize simultaneously both regional and gradient information in the processing of image segmentation.The rule is to add the weight of global information in the beginning of image segmentation,and to add the weight of local information in the second stage.The experimental results of the synthetic image and MR image segmentation show that it is often challenging to more obtain a reliable segmentation for noise and unclear edges image than the C-V method.