标题:A fusion algorithm of spatial fuzzy c-means clustering and level set for magnetic resonance image segmentation
作者:Wang, Zhihui ;Lu, Jili ;Zhang, Xiao ;Lin, Mingxing
作者机构:[Wang, Zhihui ;Zhang, Xiao ] School of Information Science and Engineering, Hebei North University, Zhangjiakou 075000, China;[Lu, Jili ;Lin, Mingxing 更多
通讯作者:Zhang, X
来源:Journal of Computational Information Systems
出版年:2014
卷:10
期:11
页码:4675-4682
DOI:10.12733/jcis10333
关键词:Fusion; Image segmentation; Level set; Magnetic resonance image; Spatial fuzzy c-means cluster
摘要:Magnetic resonance images (MRI) are widely used in medical diagnosis. However, the spatial resolution is not ideal with noises and special points, so it is di_cult to be processed by traditional image methods. This paper proposes a method which integrates fuzzy c-means clustering and level set with spatial information for magnetic resonance image segmentation. The magnetic resonance image is clustered by fuzzy c-means clustering with considering the spatial information to improve the anti-interference of the image, the result of clustering is evolved by level set to get an accurate segmented boundary. The improved method can not only increase the robust of images but also improve the processing speed. The results show that the proposed method has good segmentation quality and effciency for MRI image. © 2014 Binary Information Press.
收录类别:EI;SCOPUS
Scopus被引频次:5
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84904757601&doi=10.12733%2fjcis10333&partnerID=40&md5=f3ccf21544a8d10b185053b129e5e500
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