现代电子技术Issue(6)：90-93,4.
基于WFCM算法在MRI图像分割中的应用
Application of an improved WFCM-based algorithm in MRI image segmentation
摘要
Abstract
Fuzzy C⁃means clustering(FCM)algorithm is an unsupervised clustering algorithm. The sample weighted fuzzy C⁃means clustering(WFCM)algorithm is an improved FCM algorithm,which can significantly improve the speed of convergence and accuracy of clustering. Both FCM algorithm and WFCM algorithm are relatively sensitive to noise,but still need to deter⁃mine the number of the clusters manually. In this paper,an improved algorithm is proposed,in which the noise reduction algo⁃rithm of partial differential equations(PDE)is used to process the original brain MRI image,and the cluster validity is adopted to determine the optimal number of clusters to improve WFCM algorithm and execute the image segmentation. Experiment results show that the improved algorithm has a capability of automatic classification and better noise immunity.关键词
图像分割/PDE降噪/聚类有效性/样本加权/模糊聚类Key words
image segmentation/PDE noise reduction/validity of clustering/sample weighting/fuzzy clustering分类
信息技术与安全科学引用本文复制引用
韩红伟,苗加庆..基于WFCM算法在MRI图像分割中的应用[J].现代电子技术,2015,(6):90-93,4.基金项目
四川省教育厅基金资助项目（14ZB0355）；乐山市科技局重点项目（13GZD039）；成都理工大学工程技术学院校青年科研基金 （）
