[1]CHENG Xian-yi,GONG Xiang-pu.An improved fuzzy Cmeans algorithm for segmentation of medical images[J].CAAI Transactions on Intelligent Systems,2010,5(1):80-84.
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An improved fuzzy Cmeans algorithm for segmentation of medical images

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 5 Number of periods: 2010 1 Page number: 80-84 Column: 学术论文—机器学习 Public date: 2010-02-25
Title:
An improved fuzzy Cmeans algorithm for segmentation of medical images
Author(s):
CHENG Xian-yi;  GONG Xiang-pu
School of Computer Science and Technology, Nantong University, Nantong 226019, China
Keywords:
ant colony algorithm;  medical image segmentation;  fuzzy Cmeans clustering;  genetic algorithm
CLC:
TP391
DOI:
-
Abstract:
Stochastic selection of a clustering center would cause the iterative process to become trapped in a local extremum. To overcome this image segmentation problem, a hybrid method was proposed. It combined an ant colony algorithm with dynamic fuzzy clustering analysis. Thus the superior ability of the ant colony algorithm became available for dealing with local extrema. The resulting algorithm dynamically determined the number of clusters as well as clustering centers. Within the optimization procedure, we introduced a crowd degree function to improve the convergence rate. In addition, the parallelism and positive feedback effect of ant colony algorithm were employed to increase clustering precision. The proposed algorithm was used in the segmentation of medical images. A series of comparative experiments showed that the algorithm has improved ability to detect fuzzy or thin edges.
References:
［1］黄国瑞,王绪法,高宪斌.基于方向信息素扩散的蚁群优化算法［J］. 电子学报, 2006, 15(3): 447450.
HUANG Guorui, WANG Xufa, GAO Xianbin. Ant colony optimization algorithm based on directional pheromone diffusion［J］. Chinese Journal of Electronics, 2006, 15(3): 447450.
［2］陈小波,程显毅.一种基于MAS的自适应图像分割方法［J］. 智能系统学报, 2007, 2(4): 8085.
CHEN Xiaobo, CHENG Xianyi. An adaptive image segmentation technique based on multiAgent system［J］. CAAI Transactions on Intelligent Systems, 2007, 2(4): 8085.
［3］李旭苏,焦淑红,王立??? 王莹? .基于PSO和加权FCM的图像分割算法［J］.应用科技, 2008, 35(4): 2629.
LI Xusu, JIAO Shuhong, WANG Liying.PSO and weighted FCM based image segmentation algorithm［J］.Applied Science and Technology, 2008, 35(4): 2629.
［4］杨立才,赵莉娜,吴晓晴.基于蚁群算法的模糊C均值聚类医学图像分割［J］. 山东大学学报：工学版, 2007, 37(3): 5154.
?YANG Licai, ZHAO Lina, WU Xiaoqing. Medical image segmentation of fuzzy Cmeans clustering based on the ant colony algorithm［J］. Journal of Shandong University: Engineering Science, 2007, 37(3): 5154.
［5］王科俊,郭庆昌.基于粒子群优化算法和改进的Snake模型的图像分割算法［J］. 智能系统学报, 2007, 2(1): 5358.
WANG Kejun, GUO Qingchang. Image segmentation algorithm based on the PSO and improved Snake model［J］. CAAI Transactions on Intelligent Systems, 2007, 2(1): 5358.
［6］CHENG Xianyi, HAN Lanjun, MA Shouming. Design and realization of medical image nonrigid matching algorithm［C］//Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications. Jinan, China, 2006: 497501.
［7］程显毅,陈小波.基于多Agent的模式识别框架［J］. 智能系统学报, 2006, 1(2): 8993.
CHENG Xianyi, CHEN Xiaobo. Frame of pattern recognition based on multiAgent［J］. CAAI Transactions on Intelligent Systems, 2006, 1(2): 8993.
［8］程显毅,梁 军,马首明. 基于MAS的医学图像进化分割算法的研究［J］. 南京大学学报: 自然科学, 2008, 44(5): 503511.
CHENG Xianyi, LIANG Jun, MA Shouming. Evolutional algorithm of medical image segmentation based on a multiAgent system［J］. Journal of Nanjing University: Natural Sciences, 2008, 44(5): 503511.
［9］吴启迪,汪 镭. 智能蚁群算法及应用［M］. 上海:上海科技教育出版社, 2004: 7892.
［10］修春波,张雨虹. 基于蚁群与鱼群的混合优化算法［J］. 计算机工程, 2008, 34(14): 206207.
XIU Chunbo, ZHANG Yuhong. Hybrid optimization algorithm based on ant colony and fish school［J］. Computer Engineering, 2008, 34(14): 206207.
［11］白 杨,孙 跃,王 君,等. 基于动态自适应蚁群算法的MRI图像分割［J］.计算机科学, 2008, 35(12): 226230.
BAI Yang, SUN Yue, WANG Jun, et al. Segmentation of MRI based on dynamic and adaptive ant colony algorithm［J］. Computer Science, 2008, 35(12): 226230.
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