A novel segmentation method for MR brain images based on fuzzy connectedness and FCM

作者：Fan, Xian^*; Yang, Jie^*; Cheng, Lishui^*

来源：Second International Confernce on Fuzzy Systems and Knowledge Discovery, FSKD 2005, China,Hunan,Changsha,Changsha, 2005-08-27 to 2005-08-29.

• Clustering algorithm
• Fuzzy c-means (FCM)
• Fuzzy connectedness algorithm
• Spatial coherence

Image segmentation is an important research topic in image processing and computer vision community. In this paper, a new unsupervised method for MR brain image segmentation is proposed based on fuzzy c-means (FCM) and fuzzy connectedness. FCM is a widely used unsupervised clustering algorithm for pattern recognition and image processing problems. However, FCM does not consider the spatial coherence of images and is sensitive to noise. On the other hand, fuzzy connectedness method has achieved good performance for medical image segmentation. However, in the computation of fuzzy connectedness, one needs to select seeds manually which is elaborative and time-consuming. Our new method used FCM as the first step to select salient seeded points and then applied fuzzy connectedness algorithm based on those seeds. Thus our method achieved unsupervised automatic segmentation for brain MR images. Experiments on simulated and real data sets proved it is effective and robust to noise.

• 出版日期2005
• 单位上海交通大学