| 基于子区域相似度的医学图像分割算法 |
| |
| 引用本文： | 党建武,杨旭,王阳萍.基于子区域相似度的医学图像分割算法[J].计算机应用,2010,30(9):2458-2460. |
| |
| 作者姓名： | 党建武 杨旭 王阳萍 |
| |
| 作者单位： | 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 |
| |
| 基金项目： | 国家863计划项目，国家自然科学基金资助项目，甘肃省科技攻关计划项目，甘肃省自然科学基金资助项目 |
| |
| 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 |
| 收稿时间： | 2010-03-17 |
| 修稿时间： | 2010-05-10 |
New medical image segmentation algorithm based on subregion similarity |
| |
| DANG Jian-wu,YANG Xu,WANG Yang-ping.New medical image segmentation algorithm based on subregion similarity[J].journal of Computer Applications,2010,30(9):2458-2460. |
| |
| Authors: | DANG Jian-wu YANG Xu WANG Yang-ping |
| |
| 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. |
| |
| Keywords: | image segmentation sub-region similarity contour approximating region growing |
| 本文献已被 万方数据 等数据库收录！ |
| 点击此处可从《计算机应用》浏览原始摘要信息 |
|
点击此处可从《计算机应用》下载全文 |
