Literature DB >> 17354714

A generalized level set formulation of the Mumford-Shah functional for brain MR image segmentation.

Lishui Cheng1, Jie Yang, Xian Fan, Yuemin Zhu.   

Abstract

Brain MR image segmentation is an important research topic in medical image analysis area. In this paper, we propose an active contour model for brain MR image segmentation, based on a generalized level set formulation of the Mumford-Shah functional. The model embeds explicitly gradient information into the Mumford-Shah functional, and incorporates in a generic framework both regional and gradient information into segmentation process simultaneously. The proposed method has been evaluated on real brain MR images and the obtained results have shown the desirable segmentation performance.

Mesh:

Year:  2005        PMID: 17354714     DOI: 10.1007/11505730_35

Source DB:  PubMed          Journal:  Inf Process Med Imaging        ISSN: 1011-2499


  3 in total

1.  Semi-automatic segmentation software for quantitative clinical brain glioblastoma evaluation.

Authors:  Ying Zhu; Geoffrey S Young; Zhong Xue; Raymond Y Huang; Hui You; Kian Setayesh; Hiroto Hatabu; Fei Cao; Stephen T Wong
Journal:  Acad Radiol       Date:  2012-05-15       Impact factor: 3.173

2.  Automatic Brain Extraction for Rodent MRI Images.

Authors:  Yikang Liu; Hayreddin Said Unsal; Yi Tao; Nanyin Zhang
Journal:  Neuroinformatics       Date:  2020-06

3.  A new multistage medical segmentation method based on superpixel and fuzzy clustering.

Authors:  Shiyong Ji; Benzheng Wei; Zhen Yu; Gongping Yang; Yilong Yin
Journal:  Comput Math Methods Med       Date:  2014-03-09       Impact factor: 2.238

  3 in total

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