Unsupervised Segmentation of Medical Image Based on FCM and Mutual Information

摘要：

In the scope of medical image processing, segmentation is important and difficult.This paper presents a novel algorithm for segmentation of medical image.Our algorithm is formulated by combining the fuzzy c-means clustering (FCM)algorithm with the mutual information (MI) technique.The initial threshold can be chosen using FCM algorithm,and in the iteration process,an optimal threshold will be determined by maximizing the MI between the original volume and the thresholded volume.We evaluate the effectiveness of the proposed approach by applying it to the medical images, including magnetic resonance imaging (MRI),microphotographic image.The experimental results indicate that the proposed method has not only visually better or comparable segmentation effect but also,more favorably,removal ability for noise.

作者: Zhentai Lu Qianjin Feng Pengcheng Shi Wufan Chen

作者单位: School of Biomedical Engineering,Southern Medical University,Guang Zhou,China,510515 Department of Electrical and Electronic Engineering,Hong Kong University of Science and Technology,H

会议类型: 国际会议

会议名称: 2007 IEEE/ICME International Conference on Complex Medical Engineering-CME2007(CME2007 第二届国际复合医学工程学术大会)

会议地点: 北京

会议语种:英文

页码: 508-511

在线出版日期: 2007-05-23（万方平台首次上网日期，不代表论文的发表时间）