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结合蚁群算法的Snake模型的医学图像分割方法
引用本文:曹会志,王晨,罗述谦. 结合蚁群算法的Snake模型的医学图像分割方法[J]. 北京生物医学工程, 2007, 26(3): 245-248
作者姓名:曹会志  王晨  罗述谦
作者单位:首都医科大学生物医学工程学院,北京,100069;首都医科大学生物医学工程学院,北京,100069;首都医科大学生物医学工程学院,北京,100069
摘    要:图像分割是医学图像处理中一个网难而又极其重要的课题.本文提出一种新的结合Snake模型和蚁群算法的图像分割算法.Snake模型是一种将目标的轮廓模型与图像特征相匹配的分割方法,而蚁群算法可以帮助人们理解生物系统的原理以及在机器人技术、计算机图形学等领域已经得到广泛应用.本文在结合已有Snake模型和蚁群算法优点的基础上,提出了新的图像蚁群分割模型.实验结果表明,本文提出的分割方法能够比较好的保留图像的细节信息,并具有一定的抗噪声能力.

关 键 词:活动轮廓模型  蚁群算法  医学图像  图像分割
文章编号:1002-3208(2007)03-0245-04
收稿时间:2006-06-10
修稿时间:2006-06-102006-07-24

A novel image segmentation algorithm based on snake and artificial ant colony
CAO Huizhi,WANG Chen,LUO Shuqian. A novel image segmentation algorithm based on snake and artificial ant colony[J]. Beijing Biomedical Engineering, 2007, 26(3): 245-248
Authors:CAO Huizhi  WANG Chen  LUO Shuqian
Affiliation:Biomedical Engineering Institute, Capital University of Medical Sciences, Beijing 100069
Abstract:Segmentation is one of the most difficult tasks in digital image processing.This paper presents a novel segmentation algorithm,which based on snake model and artificial ant colonies Snakes are well known method for matching an object's contour model to features in an image.As pointed out by some recent literatures,the self-organizations of ants were successfully used for understanding biological systems and in many applications in robotics,computer graphics,etc.Considering the features of Snakes and artificial ant colonies,we present an extended model applied in image segmentation.The simulated results show the efficiency of the new algorithm,which is able to preserve the detail of the object and is insensitive to noise.
Keywords:active contour model   ant colonies   medical image   image segmentation
本文献已被 CNKI 维普 万方数据 等数据库收录!
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