Multiphase Image Segmentation Based on Improved Vese—Chart VariationaI Level Set Model Abstract Medical Image Segmentation is a traditional and challenging project,and a lot of new segmentation algorithms have been proposed by experts. Level set method describes the evolution of geometric active contour by pact mode and provides a stable numerical energy function of Mumford—Shah model synthetically uses the information of image’S boundary and region,and its contour evolution is not concemed to the gradient of model’gets a well result in blurred and discontinuous boundary,Chan and Vese introduce the active contour model based on simplified Mumford-Shah model(called C-V method),which can be used both in contour detection without model can well detect the vacuum of object,but have innate drawback when dealing plicated multiphase images. C—V method is extended to the variational level set model which needs multiple level set functions to segment multiphase image by Vese and method takes good result in dealing with the simple images whose pixels accord mean distribution,while bad result in dealing with the images whose pixels plicated probability this paper,the extended studies of this model here include general region model beyond its piecewise constant presumption and a general formulation for the multiphase first extension is based on maximum a posteriori of region partition and some parameters ate estimated for images with Gauss and Rayleigh second extension is based on the transformation between a natural number and binary results show that the extended Vese-Chan model correctly segments images. Key Words:Vese—Chan Model;Muitiphasel Variational Level Set Method;Image Segmentation 学位论文独创性声明、学位论文知识产权权属声明 学位论文独创性声明 本人声明,所呈交的学位论文系本人在导师指导下独立完成的研究成果。文中依法引用他人的成果,均已做出明确标注或得到许可。论文内容未包含法律意义上己属于他人的任何形式的研究成果,也不包含本人已用于其他学位申请的论文或成果。 本
