计算机应用 ›› 2010, Vol. 30 ›› Issue (9): 2458-2460.

• 计算机仿真与图形图像处理 • 上一篇    下一篇

基于子区域相似度的医学图像分割算法

党建武1,杨旭1,王阳萍2   

  1. 1. 兰州交通大学电子与信息工程学院
    2. 兰州交通大学 电子与信息工程学院
  • 收稿日期:2010-03-17 修回日期:2010-05-10 发布日期:2010-09-03 出版日期:2010-09-01
  • 通讯作者: 杨旭
  • 基金资助:
    国家863高技术研究发展计划基金项目;国家自然基金项目;甘肃省科技攻关计划项目;甘肃省自然科学基金项目

New medical image segmentation algorithm based on subregion similarity

  • Received:2010-03-17 Revised:2010-05-10 Online:2010-09-03 Published:2010-09-01
  • Contact: YANG Xu

摘要: 将传统的区域生长算法思想融入到一种轮廓线逼近方法中。通过定义子区域的相似度准则,利用围绕像素的子区域的统计相似性,作为一个初始多边形轮廓演化的驱动因子,从粗到细,实现了对目标区域的逼近分割。实验表明,所提算法具有较好的抗噪性和较高的分割效率,可以有效分割出医学图像中的目标区域。

关键词: 图像分割, 子区域相似度, 轮廓逼近, 区域生长

Abstract: Introducing the traditional region growing method into a contour approximating method, a new segmentation algorithm based on subregion similarity was presented. Firstly, an initial polygon contour was brought in by human-computer interactive process. Then the region of interest was obtained by using a sub-region similarity which served as driving force of the contour evolution. The experimental results show that the algorithm is of more anti-noise ability than the region growing method, and can divide up the region of interest efficiently.

Key words: image segmentation, sub-region similarity, contour approximating, region growing

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