Segmentation of retinal blood vessels using the radial projection and semi-supervised approach

doi:10.1016/j.patcog.2011.01.007

OPT OpenIR > 光谱成像技术研究室

	Segmentation of retinal blood vessels using the radial projection and semi-supervised approach
	You, Xinge 2; Peng, Qinmu 2; Yuan, Yuan1 ; Cheung, Yiu-ming 3; Lei, Jiajia 2
作者部门	光学影像分析与学习中心
	2011-10-01
发表期刊	PATTERN RECOGNITION
ISSN	0031-3203
卷号	44 期号:10-11 页码:2314-2324
摘要	Automatic segmentation of retinal blood vessels has become a necessary diagnostic procedure in ophthalmology. The blood vessels consist of two types of vessels, i.e., thin vessels and wide vessels. Therefore, a segmentation method may require two different processes to treat different vessels. However, traditional segmentation algorithms hardly draw a distinction between thin and wide vessels, but deal with them together. The major problems of these methods are as follows: (1) If more emphasis is placed on the extraction of thin vessels, the wide vessels tend to be over detected; and more artificial vessels are generated, too. (2) If more attention is paid on the wide vessels, the thin and low contrast vessels are likely to be missing. To overcome these problems, a novel scheme of extracting the retinal vessels based on the radial projection and semi-supervised method is presented in this paper. The radial projection method is used to locate the vessel centerlines which include the low-contrast and narrow vessels. Further, we modify the steerable complex wavelet to provide better capability of enhancing vessels under different scales, and construct the vector feature to represent the vessel pixel by line strength. Then, semi-supervised self-training is used for extraction of the major structures of vessels. The final segmentation is obtained by the union of the two types of vessels. Our approach is tested on two publicly available databases. Experiment results show that the method can achieve improved detection of thin vessels and decrease false detection of vessels in pathological regions compared to rival solutions. (C) 2011 Published by Elsevier Ltd.
文章类型	Article
关键词	Radial Projection Retinal Images Steerable Complex Wavelet
WOS标题词	Science & Technology ; Technology
DOI	10.1016/j.patcog.2011.01.007
收录类别	SCI ; EI
关键词[WOS]	VASCULAR SEGMENTATION ; MATCHED-FILTERS ; IMAGES ; CLASSIFICATION ; MODEL ; ALGORITHM ; WAVELET
语种	英语
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号	WOS:000292849000010
引用统计	被引频次：290[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.opt.ac.cn/handle/181661/10571
专题	光谱成像技术研究室
作者单位	1.Chinese Acad Sci, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Ctr OPT IMagery Anal & Learning OPTIMAL, Xian 710119, Shaanxi, Peoples R China 2.Huazhong Univ Sci & Technol, Dept Elect & Informat Engn, Wuhan 430074, Peoples R China 3.Hong Kong Baptist Univ, Dept Comp Sci, Hong Kong, Hong Kong, Peoples R China
推荐引用方式 GB/T 7714	You, Xinge,Peng, Qinmu,Yuan, Yuan,et al. Segmentation of retinal blood vessels using the radial projection and semi-supervised approach[J]. PATTERN RECOGNITION,2011,44(10-11):2314-2324.
APA	You, Xinge,Peng, Qinmu,Yuan, Yuan,Cheung, Yiu-ming,&Lei, Jiajia.(2011).Segmentation of retinal blood vessels using the radial projection and semi-supervised approach.PATTERN RECOGNITION,44(10-11),2314-2324.
MLA	You, Xinge,et al."Segmentation of retinal blood vessels using the radial projection and semi-supervised approach".PATTERN RECOGNITION 44.10-11(2011):2314-2324.

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