医学图像分割中的主动轮廓模型研究现状  

A Review of the Active Contour Models in Medical Image Segmentation

作　　者：陈明[1] 赵云[1] 范能胜[1] 张怀岺[1] 

机构地区：[1]广东医学院生物医学工程教研室,广东东莞523808

出　　处：《北京生物医学工程》2010年第4期426-431,共6页Beijing Biomedical Engineering

基　　金：广东东莞市高校科技计划项目(200910815252)资助

摘　　要：主动轮廓模型具有强大的先验知识引入能力,非常适合解决复杂医学图像分割问题。本文介绍了两种主动轮廓模型的基本原理及其相互关系,详细综述了模型的几个重要改进措施,包括曲线的表示方式、基于梯度的ACM、基于区域的ACM,以及结合先验形状的ACM,并讨论了医学图像分割中的主要应用实例,最后展望了模型今后的研究方向。The active contour models （ACM） are especially adapted to the complicated medical image segmentation, because of the powerful ability of incorporating prior knowledge. In this paper, the basic principles and the relationship of two kinds of the ACM were introduced briefly. Then several important improvement schemes were reviewed in detail, including the representations of curves, the gradient-based ACM, the region-based ACM, and the ACM incorporating prior shape information. After that several main applications in medical image segmentation were discussed. The future research work about the ACM was presented in the end.

关 键 词：主动轮廓模型 图像分割 水平集方法 

分 类 号：R318.04[医药卫生—生物医学工程]