Novel method of MRI medical image segmentation combining watershed algorithm and WKFCM algorithm

摘要：

　　Aimed at the disadvantage of over-segmentation that traditional watershed algorithm segmented MRI images,a new method of MRI image segmentation was presented.First,through traditional watershed segmentation algorithm,the image was segmented into different areas,and then based on the improved kernel-clustering algorithm,we used Mercer-kernel to map average gray value of each area to high-dimensional feature space,making originally not displayed features manifested.In this way,we can achieve a more accurate clustering,and solve over-segmentation problem of watershed algorithm segmenting MRI images efficiently,thereby get better segmentation result.Experimental results show that the method of this paper can segment brain MRI images satisfactorily,and obtain clearer segmentation images.

关键词： Watershed algorithm Mercer-kernel High-dimensional feature space WKFCM algorithm MRI image segmentation

作者: Jinqing Liu Kun Chen

作者单位: School of Physics and Opto-Electronics Technology, Fujian Normal University,Fuzhou, Fujian, China, 350007

会议类型: 国际会议

会议名称: the Second International Conference on Frontiers of Manufacturing and Design Science(第二届制造与设计科学国际会议(ICFMD 2011))

会议地点: 台湾

会议语种:英文

页码: 4518-4522

在线出版日期: 2011-12-11（万方平台首次上网日期，不代表论文的发表时间）