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基于近似密度函数的医学图像聚类分析研究
引用本文:宋余庆,谢从华,朱玉全,李存华,陈健美,王立军.基于近似密度函数的医学图像聚类分析研究[J].计算机研究与发展,2006,43(11):1947-1952.
作者姓名:宋余庆  谢从华  朱玉全  李存华  陈健美  王立军
作者单位:1. 江苏大学计算机科学与通信工程学院,镇江,212013
2. 常熟理工学院计算机系,常熟,215500
3. 淮海工学院计算机科学系,连云港,222005
基金项目:国家自然科学基金;江苏省软件与集成电路专项基金
摘    要:针对医学图像数据难以用数学模型来表述和聚类的问题,提出一种基于近似密度函数的医学图像聚类分析方法.该方法采用核密度估计模型来构造近似密度函数,利用爬山策略来提取聚类模式.基于真实的人体腹部医学图像数据集的实验结果表明,该方法可以取得较好的聚类效果.

关 键 词:密度估计  医学图像  聚类分析  爬山算法
收稿时间:05 31 2006 12:00AM
修稿时间:2006-05-312006-09-14

Research on Medical Image Clustering Based on Approximate Density Function
Song Yuqing,Xie Conghua,Zhu Yuquan,Li Cunhua,Chen Jianmei,Wang Lijun.Research on Medical Image Clustering Based on Approximate Density Function[J].Journal of Computer Research and Development,2006,43(11):1947-1952.
Authors:Song Yuqing  Xie Conghua  Zhu Yuquan  Li Cunhua  Chen Jianmei  Wang Lijun
Affiliation:1. School of Computer Science and Communications Engineering, Jiangsu University, Zhenjiang 212013;2. Department of Computer Science , Changshu Institute of Technology, Changshu 215500;3.Department of Computer Science, Huaihai Institute of Technology, Lianyungang 222005
Abstract:It is difficult to represent and cluster medical image data by mathematic model. In order to address this problem, an medical image clustering analysis method based on approximate density function is designed. This method uses kernel density estimation model to construct the approximate density function, and takes hill climbing strategy to extract clustering patterns. Results of experiments show that it can achieve good effect on real human abdomen medical images.
Keywords:density estimation  medical image  clustering analysis  hill climbing
本文献已被 CNKI 维普 万方数据 等数据库收录!
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