Medical image segmentation using improved FCM  

作　　者：ZHANG XiaoFeng ZHANG CaiMing TANG WenJing WEI ZhenWen 

机构地区：[1]School of Computer Science and Technology,Shandong University,Jinan 250101,China [2]School of Information and Electrical Engineering,Ludong University,Yantai 264025,China [3]School of Computer Science and Technology,Shandong University of Finance and Economics,Jinan 250014,China [4]Shandong Province Key Lab of Digital Media Technology,Jinan 250014,china

出　　处：《Science China(Information Sciences)》2012年第5期1052-1061,共10页中国科学（信息科学）（英文版）

基　　金：supported by National Natural Science Foundation of China (Grant Nos. 61020106001,60933008,60903109,61170161);National Science & Technology Pillar Program in the Twelfth Five-year Plan Period (Grant No.2011BAD21B01);Technology Development Programe of Shandong Province (Grant Nos. 2008-GGB01814,2011GGB01193,2011GGB01138);Natural Science Foundation of Ludong University (Grant No.LY2010014)

摘　　要：Image segmentation is one of the most important problems in medical image processing,and the existence of partial volume effect and other phenomena makes the problem much more complex.Fuzzy C-means,as an effective tool to deal with PVE,however,is faced with great challenges in efficiency.Aiming at this,this paper proposes one improved FCM algorithm based on the histogram of the given image,which will be denoted as HisFCM and divided into two phases.The first phase will retrieve several intervals on which to compute cluster centroids,and the second one will perform image segmentation based on improved FCM algorithm.Compared with FCM and other improved algorithms,HisFCM is of much higher efficiency with satisfying results.Experiments on medical images show that HisFCM can achieve good segmentation results in less than 0.1 second,and can satisfy real-time requirements of medical image processing.

关 键 词：FCM HISTOGRAM image segmentation medical image processing 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TN911.73[自动化与计算机技术—计算机科学与技术]