Unsupervised segmentation of medical image based on difference of mutual information  

作　　者：LU Qingwen CHEN Wufan 

机构地区：[1]School of BME, Southern Medical University, Guangzhou 510515, China

出　　处：《Science in China(Series F)》2006年第4期484-493,共10页中国科学（F辑英文版）

基　　金：the National Basic Research Program of China （Grant No. 2003CB716101）; the National Natural Science Foundation of China （Grant No. 30130180）.

摘　　要：In the scope of medical image processing, segmentation is important and difficult. There are still two problems which trouble us in this field. One is how to determine the number of clusters in an image and the other is how to segment medical images containing lesions. A new segmentation method called DDC, based on difference of mutual information （dMI） and pixon, is proposed in this paper. Experiments demonstrate that dMI shows one kind of intrinsic relationship between the segmented image and the original one and so it can be used to well determine the number of clusters. Furthermore, multi-modality medical images with lesions can be automatically and successfully segmented by DDC method.In the scope of medical image processing, segmentation is important and difficult. There are still two problems which trouble us in this field. One is how to determine the number of clusters in an image and the other is how to segment medical images containing lesions. A new segmentation method called DDC, based on difference of mutual information （dMI） and pixon, is proposed in this paper. Experiments demonstrate that dMI shows one kind of intrinsic relationship between the segmented image and the original one and so it can be used to well determine the number of clusters. Furthermore, multi-modality medical images with lesions can be automatically and successfully segmented by DDC method.

关 键 词：medical image unsupervised segmentation mutual information pixon. 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]