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多速度函数水平集算法及在医学分割中的应用
引用本文:陈健,田捷,薛健,戴亚康.多速度函数水平集算法及在医学分割中的应用[J].软件学报,2007,18(4):842-849.
作者姓名:陈健  田捷  薛健  戴亚康
作者单位:中国科学院,自动化研究所,复杂系统与智能科学重点实验室,医学影像研究室,北京,100080;中国科学院,研究生院,北京,100049
基金项目:国家自然科学基金;国家重点基础研究发展计划(973计划);国家高技术研究发展计划(863计划);国家科技支撑计划;海外青年学者合作研究基金;北京市自然科学基金
摘    要:以往的水平集算法都只有一个单一的速度函数,在零水平集的演化过程中,能量函数最小化是一个很复杂的过程,而单一的速度函数存在很多问题.在此基础上,根据不同分割区域属性的异同,提出了一种具有多个速度函数的多水平集分割算法:以不同的待分割区域构造多个不同的水平集函数,相应地构造多个不同的速度函数.多个零水平集同时演化,相互作用,以达到分割的目的.该方法不但提高了分割的精度,而且能够很好地解决单一速度函数水平集算法难以处理的边界缺口问题.将此算法应用于医学MRI和CT的图像分割,得到了很好的分割结果.

关 键 词:水平集  图像分割  速度函数  能量函数
收稿时间:2006-04-18
修稿时间:2006-05-30

Levelset Method with Multi-Speed-Function and Its Application in Segmentation of Medical Images
CHEN Jian,TIAN Jie,XUE Jian and DAI Ya-Kang.Levelset Method with Multi-Speed-Function and Its Application in Segmentation of Medical Images[J].Journal of Software,2007,18(4):842-849.
Authors:CHEN Jian  TIAN Jie  XUE Jian and DAI Ya-Kang
Affiliation:1.Medical Image Processing Group, Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, The Chinese Academy of Sciences, Beijing 100080, China; 2.Graduate School, The Chinese Academy of Sciences, Beijing 100049, China
Abstract:All of the former level set algorithms have only one level set function and only one speed function, and it is a complex procedure to minimize the energy function during the evolvement of the zero-level-set. Furthermore, there are a lot of problems in this single speed function. In this paper, a new multi-level-set algorithm with multiplicate speed functions is proposed according to the different properties of different objects: Different level set functions are constructed in different regions, and so are different speed functions accordingly; many zero-level-sets are evolved at the same time and act on one another in order to segment. This method not only enhances the accuracy of segmentation, but also solves the bounder gap problem well, which is quite a puzzle for single level set algorithm. Perfect results are achieved when this method is applied to segment the MR and CT images.
Keywords:MRI(magnetic resonance image)
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