Coronary Artery Fibrous Plaque Detection Based on Multi-Scale Convolutional Neural Networks

doi:10.1007/s11265-019-01501-5

CORC > 计算技术研究所 > 中国科学院计算技术研究所 > 中国科学院计算技术研究所期刊论文 > 英文

	Coronary Artery Fibrous Plaque Detection Based on Multi-Scale Convolutional Neural Networks
	Liu, Xiuling 1,3; Du, Jiaxing 1,3; Yang, Jianli 1,3; Xiong, Peng 1,3; Liu, Jing 2,3,4; Lin, Feng 5
刊名	JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY
	2020-03-01
卷号	92 期号:3 页码:325-333
关键词	Coronary heart disease Fibrous plaque Optical coherence tomography Multi-scale convolution neural networks
ISSN号	1939-8018
DOI	10.1007/s11265-019-01501-5
英文摘要	One of the major causes of the coronary heart disease is vascular stenosis and thrombosis that is generally caused by development of fibrous plaques. Therefore, detection of a fibrous plaque in coronary arteries for the diagnosis and treatment of coronary heart disease is of clinical significance. Technical challenges are in reading the optical coherence tomography (OCT) images which is tedious and inaccurate. In response, we propose an automated coronary artery fibrous plaque detection method based on deep learning with Convolutional Neural Networks (CNN). We present our novel techniques of identifying a contracting path to capture the context and a symmetric expanding path that enables the precise localization. The algorithm utilizes the features of the contracting path and the expanding path, so that the merged features can present the context and accurate localization, and uses the multi-scale feature maps for detection. Experimental results show that the proposed method achieved a coincidence of 91.04%, accuracy of 94.12%, and recall of 94.12%. Compared with the previously published work the proposed method is advantageous in both accuracy and robustness.
资助项目	National Natural Science Foundation of China[61802109] ; National Natural Science Foundation of China[61703133] ; Key Projects of Hebei Province[F2017201222] ; Natural Science Foundation of Hebei Province[F2017205066] ; Hebei Province 100 Excellent Innovative Talents Support Program[SLRC2017022] ; Scientific Research Fund of Hebei Normal University[L2017B06] ; Scientific Research Fund of Hebei Normal University[L2018K02] ; Post-graduate's Innovation Fund Project of Hebei University[hbu2019ss069] ; personnel training project of Hebei Province[A2016002012]
WOS研究方向	Computer Science ; Engineering
语种	英语
出版者	SPRINGER
WOS记录号	WOS:000519562300007
内容类型	期刊论文
源URL	[http://119.78.100.204/handle/2XEOYT63/14366]
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Liu, Jing
作者单位	1.Hebei Univ, Coll Elect Informat Engn, Baoding, Hebei, Peoples R China 2.Hebei Normal Univ, Coll Comp & Cyber Secur, Shijiazhuang, Hebei, Peoples R China 3.Hebei Univ, Key Lab Digital Med Engn Hebei Prov, Baoding, Hebei, Peoples R China 4.Chinese Acad Sci, Inst Comp Technol, Beijing Key Lab Mobile Comp & Pervas Device, Beijing, Peoples R China 5.Nanyang Technol Univ, Sch Comp Sci & Engn, Singapore, Singapore
推荐引用方式 GB/T 7714	Liu, Xiuling,Du, Jiaxing,Yang, Jianli,et al. Coronary Artery Fibrous Plaque Detection Based on Multi-Scale Convolutional Neural Networks[J]. JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY,2020,92(3):325-333.
APA	Liu, Xiuling,Du, Jiaxing,Yang, Jianli,Xiong, Peng,Liu, Jing,&Lin, Feng.(2020).Coronary Artery Fibrous Plaque Detection Based on Multi-Scale Convolutional Neural Networks.JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY,92(3),325-333.
MLA	Liu, Xiuling,et al."Coronary Artery Fibrous Plaque Detection Based on Multi-Scale Convolutional Neural Networks".JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY 92.3(2020):325-333.