OPT OpenIR  > 动态光学成像研究室
A Novel ACM for Segmentation of Medical Image with Intensity Inhomogeneity
Niu, Yuefeng1,2; Cao, Jianzhong1; Liu, Liqiang1,2; Guo, Huinan1; Niu, YF (reprint author), Chinese Acad Sci, Xian Inst Opt & Precis Mech, Xian, Shaanxi, Peoples R China.
2017
Conference Name2nd IEEE International Conference on Computational Intelligence and Applications (ICCIA)
Source Publication2017 2ND IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND APPLICATIONS (ICCIA)
Pages308-311
Conference Date2017-09-08
Conference PlaceN China Univ Technol, Beijing, PEOPLES R CHINA
Publication PlaceNEW YORK
PublisherIEEE
Contribution Rank1
Abstract

This paper presents a scheme of improvement on the Li's model in terms of intensity inhomogeneous images. By introducing local entropy to Li's model, our method is able to segment medical images with intensity inhomogeneity and estimate the bias field simultaneously. The level set energy function is redefined as a weighted energy integral, where the weight is local entropy deriving from a grey level distribution of image. The total energy functional is then incorporated into a level set formulation. Experimental results on test images show that our approach outperforms the existing locally statistical active contour model (LSACM) and Li's model in terms of accuracy and efficiency with less central processing unit (CPU) time.

KeywordImage Segmentation Intensity Inhomogeneity Level Set Local Entropy
Subject AreaComputer Science, Artificial Intelligence
Department动态光学成像研究室
Indexed ByEI ; ISTP
ISBN978-1-5386-2030-4
Language英语
Document Type会议论文
Identifierhttp://ir.opt.ac.cn/handle/181661/29961
Collection动态光学成像研究室
Corresponding AuthorNiu, YF (reprint author), Chinese Acad Sci, Xian Inst Opt & Precis Mech, Xian, Shaanxi, Peoples R China.
Affiliation1.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Xian, Shaanxi, Peoples R China
2.Univ Chinese Acad Sci, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Niu, Yuefeng,Cao, Jianzhong,Liu, Liqiang,et al. A Novel ACM for Segmentation of Medical Image with Intensity Inhomogeneity[C]. NEW YORK:IEEE,2017:308-311.
Files in This Item:
File Name/Size DocType Version Access License
A Novel ACM for Segm(486KB)会议论文 暂不开放CC BY-NC-SAApplication Full Text
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Niu, Yuefeng]'s Articles
[Cao, Jianzhong]'s Articles
[Liu, Liqiang]'s Articles
Baidu academic
Similar articles in Baidu academic
[Niu, Yuefeng]'s Articles
[Cao, Jianzhong]'s Articles
[Liu, Liqiang]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Niu, Yuefeng]'s Articles
[Cao, Jianzhong]'s Articles
[Liu, Liqiang]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.