Level Set Based on Signed Pressure Force Function and Its Application in Liver Image Segmentation

作     者：JIANG Huiyan1,2,FENG Ruijie2,3,GAO Xihe1,2 1.Software College,Northeastern University,Shenyang 110819,Liaoning,China 2.Key Laboratory of Medical Image Computing of Ministry of Education Northeastern University,Shenyang 110819,Liaoning,China 3.Sino-Dutch Biomedical and Information Engineering School,Northeastern University,Shenyang 110819,Liaoning,China 

作者机构：Software College Northeastern University Shenyang Liaoning China Key Laboratory of Medical Image Computing of Ministry of Education Northeastern University Shenyang Liaoning China Sino-Dutch Biomedical and Information Engineering School Northeastern University Shenyang Liaoning China 

出 版 物：《Wuhan University Journal of Natural Sciences》 (武汉大学学报（自然科学英文版）)

年 卷 期：2011年第16卷第3期

页      面：265-270页

学科分类：0831[工学-生物医学工程（可授工学、理学、医学学位）] 100207[医学-影像医学与核医学] 1002[医学-临床医学] 08[工学] 1010[医学-医学技术（可授医学、理学学位）] 080203[工学-机械设计及理论] 0802[工学-机械工程] 10[医学] 

基　　金：Supported by the National Natural Science Foundation of China (60973071) the Natural Science Foundation of Liaoning Province (20092004) 

主　　题：segmentation level set signed pressure force liver 

摘      要：The edge-based level set model gives no satisfactory results for images with weak edge, and the region-based model performs poorly for intensity inhomogeneity images. In this paper, we propose an improved region-based level set model that integrates both the gradient information and the region information. The proposed model defines a novel external energy term, which consists of gradient information and signed pressure forces function. In order to eliminate the re-initialization procedure of traditional level set model, an internal energy term is also introduced for the level set function to maintain signed distance function. Compared with traditional models, our model is more robust against images with weak edge and intensity inhomogeneity. Experiments on liver segmentation from abdominal CT images demonstrate the effectiveness and accuracy of the proposed method.