A Cerebrovascular Image Segmentation Method Based on Geometrical Feature Point Clustering and Local Threshold

doi:10.2174/1573405613999170922143513

	A Cerebrovascular Image Segmentation Method Based on Geometrical Feature Point Clustering and Local Threshold
	Liu, Bin 1,2; Zhu, Chen 3; Qu, Xiaofeng 4; Wang, Mingzhe 1; Zhang, Song 1; Wang, Yi 1,2; Fan, Xin 1,2; Luo, Zhongxuan 1,2; Zhang, Bingbing 5; Yue, Zongge 6
	2018
发表期刊	CURRENT MEDICAL IMAGING REVIEWS
ISSN	1573-4056
卷号	14 期号:5 页码:748-770
摘要	Background: For the cerebrovascular Digital Subtraction Angiography (DSA), how to restrain the patient motion artifact to improve the quality of subtraction image has an important effect on the clinical diagnosis. Methods: Currently, image registration is the main way to extract the blood vessels. However, there is usually massive calculation in the registration process. And it is usually only suitable for simple rigid motion artifact. Instead of registration way, a novel cerebrovascular segmentation method was proposed to extract blood vessels in this paper. In this method, the geometrical feature points of mask image and live image were firstly detected by SIFT algorithm under same restrain parameters. Secondly, the feature points were clustered and the subtraction of clustered point set was implemented. Then, the coordinates of the residual feature points were adjusted based on gray gradient. Lastly, the vessel image was segmented based on region growing and local threshold. Result: Experiments for the sequential cerebrovascular DSA images illustrate the applicability of this method. The quality of the vessel image after segmentation was satisfactory. The interdependency of geometrical feature information for both mask image and live image was adequately utilized in this new method. Conclusion: This method can provide accurate vessel image data for the clinical operation based on DSA interventional therapy.
关键词	Digital subtraction angiography cerebrovascular image segmentation feature point clustering local threshold SIFT algorithm DSA interventional therapy
DOI	10.2174/1573405613999170922143513
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61300085] ; National Natural Science Foundation of China[61572101] ; Scientific Research Fund of Liaoning Provincial Education Department of China[L2013012] ; Fundamental Research Funds for the Central Universities of China[DUT14QY18]
WOS研究方向	Radiology, Nuclear Medicine & Medical Imaging
WOS类目	Radiology, Nuclear Medicine & Medical Imaging
WOS记录号	WOS:000443684600011
出版者	BENTHAM SCIENCE PUBL LTD
引用统计	被引频次：1[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/4983
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Zhang, Bingbing
作者单位	1.Dalian Univ Technol, Int Sch Informat Sci & Engn DUT RUISE, Dalian, Peoples R China 2.Dalian Univ Technol, Key Lab Ubiquitous Network & Serv Software Liaoni, Dalian, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China 4.Dalian Med Univ, Hosp 2, Dalian, Peoples R China 5.Dalian Med Univ, Modern Technol & Educ Dept, Dalian, Peoples R China 6.Dalian Univ Technol, Affiliated Hosp, Dalian, Peoples R China
推荐引用方式 GB/T 7714	Liu, Bin,Zhu, Chen,Qu, Xiaofeng,et al. A Cerebrovascular Image Segmentation Method Based on Geometrical Feature Point Clustering and Local Threshold[J]. CURRENT MEDICAL IMAGING REVIEWS,2018,14(5):748-770.
APA	Liu, Bin.,Zhu, Chen.,Qu, Xiaofeng.,Wang, Mingzhe.,Zhang, Song.,...&Yue, Zongge.(2018).A Cerebrovascular Image Segmentation Method Based on Geometrical Feature Point Clustering and Local Threshold.CURRENT MEDICAL IMAGING REVIEWS,14(5),748-770.
MLA	Liu, Bin,et al."A Cerebrovascular Image Segmentation Method Based on Geometrical Feature Point Clustering and Local Threshold".CURRENT MEDICAL IMAGING REVIEWS 14.5(2018):748-770.