首页    期刊浏览 2024年11月27日 星期三
登录注册

文章基本信息

  • 标题:Liver Segmentation from CT Image Using Fuzzy Clustering and Level Set
  • 本地全文:下载
  • 作者:Xuechen Li ; Suhuai Luo ; Jiaming Li
  • 期刊名称:Journal of Signal and Information Processing
  • 印刷版ISSN:2159-4465
  • 电子版ISSN:2159-4481
  • 出版年度:2013
  • 卷号:04
  • 期号:03
  • 页码:36-42
  • DOI:10.4236/jsip.2013.43B007
  • 语种:English
  • 出版社:Scientific Research Publishing
  • 摘要:This paper presents a fully automatic segmentation method of liver CT scans using fuzzy c-mean clustering and level set. First, the contrast of original image is enhanced to make boundaries clearer; second, a spatial fuzzy c-mean clustering combining with anatomical prior knowledge is employed to extract liver region automatically; thirdly, a distance regularized level set is used for refinement; finally, morphological operations are used as post-processing. The experiment result shows that the method can achieve high accuracy (0.9986) and specificity (0.9989). Comparing with standard level set method, our method is more effective in dealing with over-segmentation problem.
  • 关键词:Liver Segmentation; Fuzzy c-Mean Clustering; Level Set
国家哲学社会科学文献中心版权所有