A Novel Active Contour Model for Medical Image Segmentation  

作　　者：付增良 叶铭 苏永琳 林艳萍 王成焘 

机构地区：[1]Institute of Biomedical Manufacturing and Life Quality Engineering,Shanghai Jiaotong University

出　　处：《Journal of Shanghai Jiaotong university(Science)》2010年第5期549-555,共7页上海交通大学学报（英文版）

基　　金：the National Natural Science Foundation of China (Nos.30801302 and 30872906);the "Medical and Engineering Crossing" Foundation of Shanghai Jiaotong University (No.40YG2009ZD102)

摘　　要：A novel segmentation method for medical image with intensity inhomogeneity is introduced.In the proposed active contour model,both region and gradient information are taken into consideration.The former,i.e.,region-based fitting energy,draws upon the region information and guarantees the accurate extraction of inhomogeneous image's local information.The latter,i.e.,an edge indicator,weights the length penalizing term to consider the gradient constrain.Moreover,signed distance penalizing term is also added to ensure accurate computation and avoid the time-consuming re-initialization of evolving level set function.Experiments for synthetic and real images demonstrate the feasibility and superiority of the proposed model.A novel segmentation method for medical image with intensity inhomogeneity is introduced. In the proposed active contour model, both region and gradient information are taken into consideration. The former, i.e., region-based fitting energy, draws upon the region information and guarantees the accurate extraction of inhomogeneous image＇s local information. The latter, i.e., an edge indicator, weights the length penalizing term to consider the gradient constrain. Moreover, signed distance penalizing term is also added to ensure accurate computation and avoid the time-consuming re-initialization of evolving level set function. Experiments for synthetic and real images demonstrate the feasibility and superiority of the proposed model.

关 键 词：image segmentation active contour intensity inhomogeneity region-based fitting energy edge indicator 

分 类 号：TP394.41[自动化与计算机技术—计算机应用技术]