基于复合矢量场的改进ACM模型与医学图像分割  

Improved compound vector field based ACM model and medical image segmentation

作　　者：高杨[1] 秦安[1] 冯前进[1] 陈武凡[1] 

机构地区：[1]南方医科大学生物医学工程学院医学信息所,广州510515

出　　处：《计算机工程与应用》2007年第22期231-234,共4页Computer Engineering and Applications

基　　金：国家重点基础研究发展规划(973)(the National Grand Fundamental Research 973 Program of China under Grant No.2003CB716104)。

摘　　要：提出了一种基于复合矢量场的改进ACM模型分割算法。采用广义模糊理论对图像进行处理,得到较理想的边缘映射图,在此基础上构建一个复合矢量场替代原有的力场,使得图像的分割结果有了较大的改进。实验结果证明,该算法能在较大范围内捕获图像的特征、较好地处理深度凹陷区域和大曲率边缘的能力。An improved Active Contours Model （ACM） model algorithm for image segmentation based on the compound vector field is proposed.The image is processed by the generalized fuzzy theory to get a better edge map.The improved ACM model achieve a better effect on image segmentation by replacing the traditional GVF with the compound vector field.The segmentation experiments show that the algorithm has brilliant capacity of not only capturing the image feature in a wider region but also dealing with the concave regions.

关 键 词：ACM模型 广义模糊 复合矢量场 医学图像分割 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]