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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
会议名称2nd IEEE International Conference on Computational Intelligence and Applications (ICCIA)
会议录名称2017 2ND IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND APPLICATIONS (ICCIA)
页码308-311
会议日期2017-09-08
会议地点N China Univ Technol, Beijing, PEOPLES R CHINA
出版地NEW YORK
出版者IEEE
产权排序1
摘要

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.

关键词Image Segmentation Intensity Inhomogeneity Level Set Local Entropy
学科领域Computer Science, Artificial Intelligence
作者部门动态光学成像研究室
收录类别EI ; ISTP
ISBN号978-1-5386-2030-4
语种英语
文献类型会议论文
条目标识符http://ir.opt.ac.cn/handle/181661/29961
专题动态光学成像研究室
通讯作者Niu, YF (reprint author), Chinese Acad Sci, Xian Inst Opt & Precis Mech, Xian, Shaanxi, Peoples R China.
作者单位1.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Xian, Shaanxi, Peoples R China
2.Univ Chinese Acad Sci, Beijing, Peoples R China
推荐引用方式
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.
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