- Title
- Liver segmentation from CT Image using fuzzy clustering and level set
- Creator
- Li, Xuechen; Luo, Suhuai; Li, Jiaming
- Relation
- Journal of Signal and Information Processing Vol. 4, Issue 3BB, p. 36-42
- Publisher Link
- http://dx.doi.org/10.4236/jsip.2013.43B007
- Publisher
- Scientific Research Publishing
- Resource Type
- journal article
- Date
- 2013
- Description
- 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 cluster- ing 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 experi- ment result shows that the method can achieve high accuracy (0.9986) and specificity (0.9989). Comparing with stan- dard level set method, our method is more effective in dealing with over-segmentation problem.
- Subject
- liver segmentation; fuzzy c-mean clustering; level set
- Identifier
- http://hdl.handle.net/1959.13/1341432
- Identifier
- uon:28740
- Identifier
- ISSN:2159-4465
- Rights
- Copyright © 2013 Xuechen Li, Suhuai Luo, Jiaming Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- Language
- eng
- Full Text
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