A NEW DEFORMABLE MODEL USING LEVEL SETS FOR SHAPE SEGMENTATION  

作　　者：He Ning Zhang Peng Lu Ke 

机构地区：[1]School of Mathematical Sciences, Capital Normal University, Beijing 100037, China [2]College of Computing ＆ Communication Engineering, Graduate University of Chinese Academy of Sciences, Beijing 100049, China

出　　处：《Journal of Electronics(China)》2009年第3期353-358,共6页电子科学学刊（英文版）

基　　金：Supported by the National Natural Science Foundation of China (No.60472071, 60532080, 60602062);the Natural Science Foundation of Beijing (No.4051002)

摘　　要：In this paper, we present a new deformable model for shape segmentation, which makes two modifications to the original level set implementation of deformable models.The modifications are motivated by difficulties that we have encountered in applying deformable models to segmentation of medical images.The level set algorithm has some advantages over the classical snake deformable models.However, it could develop large gaps in the boundary and holes within the objects.Such boundary gaps and holes of objects can cause inaccurate segmentation that requires manual correction.The proposed method in this paper possesses an inherent property to detect gaps and holes within the object with a single initial contour and also does not require specific initialization.The first modification is to replace the edge detector by some area constraint, and the second modification utilizes weighted length constraint to regularize the curve under evolution.The proposed method has been applied to both synthetic and real images with promising results.In this paper, we present a new deformable model for shape segmentation, which makes two modifications to the original level set implementation of deformable models. The modifications are motivated by difficulties that we have encountered in applying deformable models to segmentation of medical images. The level set algorithm has some advantages over the classical snake deformable models. However, it could develop large gaps in the boundary and holes within the objects. Such boundary gaps and holes of objects can cause inaccurate segmentation that requires manual correction. The proposed method in this paper possesses an inherent property to detect gaps and holes within the object with a single initial contour and also does not require specific initialization. The first modification is to replace the edge detector by some area constraint, and the second modification utilizes weighted length constraint to regularize the curve under evolution. The proposed method has been applied to both synthetic and real images with promising results.

关 键 词：Image segmentation Level sets CONSTRAINT Deformable model 

分 类 号：TN919.81[电子电信—通信与信息系统] TP391.41[电子电信—信息与通信工程]