Localization of myocardial infarction using a multi-branch weight sharing network based on 2-D vectorcardiogram

doi:10.1016/j.engappai.2022.105428

CORC > 自动化研究所 > 中国科学院自动化研究所 > 复杂系统管理与控制国家重点实验室 > 先进机器人控制团队

	Localization of myocardial infarction using a multi-branch weight sharing network based on 2-D vectorcardiogram
	He, Cong 3,4; Liu, Ming 4; Xiong, Peng 4; Yang, Jianli 4; Du, Haiman 4; Xu, Jinpeng 2; Hou, Zengguang 1; Liu, Xiuling 4
刊名	ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
	2022-11-01
卷号	116 页码:9
关键词	Vectorcardiogram Myocardial infarction Multi-branch neural network Weight sharing
ISSN号	0952-1976
DOI	10.1016/j.engappai.2022.105428
通讯作者	Liu, Xiuling(liuxiuling121@hotmail.comm)
英文摘要	Early diagnosis and localization of myocardial infarction (MI) assist clinicians in saving numerous lives through the timely treatment for patients with MI. Vectorcardiogram (VCG) can reflect the characteristic changes of cardiac electrical activity in MI in detail. In this context, the present study reports a multi-branch weight sharing network model based on 2-D VCG constructed to realize the automatic localization of MI. The three -branch network extracted the spatial morphological features of the three planes of the 2-D VCG, respectively, and the weight-sharing part of the network obtained the spatial correlation information among the three planes. Subsequently, the Softmax classifier was employed to classify normal individuals and MI patients (11 class infarct sites). To evaluate the performance of the proposed method for MI localization, PTB(Physikalisch-Technische Bundesanstalt) diagnostic ECG database was employed. The localization accuracy, sensitivity, and specificity achieved using the proposed method were 99.87%, 99.92%, and 99.99%, respectively. Thus, the proposed scheme is expected to be useful in assisting cardiologists in interpreting VCG for clinical diagnosis.
资助项目	National Natural Science Foundation of China ; Nat-ural Science Foundation of Hebei Province ; Youth Talent Support Program of Hebei Province ; Science and Technology Research Project of Higher Education Institution of Hebei Province ; Key project of Science and Technol-ogy for Higher Education Institutions in Hebei Province ; [U20A20224] ; [62006067] ; [F2021201008] ; [BJ2019044] ; [QN2020428] ; [ZD2021013]
WOS关键词	ECG ; DYNAMICS
WOS研究方向	Automation & Control Systems ; Computer Science ; Engineering
语种	英语
出版者	PERGAMON-ELSEVIER SCIENCE LTD
WOS记录号	WOS:000876457200011
资助机构	National Natural Science Foundation of China ; Nat-ural Science Foundation of Hebei Province ; Youth Talent Support Program of Hebei Province ; Science and Technology Research Project of Higher Education Institution of Hebei Province ; Key project of Science and Technol-ogy for Higher Education Institutions in Hebei Province
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/50669]
专题	自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队
通讯作者	Liu, Xiuling
作者单位	1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 2.Hebei Univ, Affiliated Hosp, Baoding 071002, Peoples R China 3.Hebei Univ, Sch Qual & Tech Supervis, Baoding 071002, Peoples R China 4.Hebei Univ, Coll Elect & Informat Engn, Key Lab Digital Med Engn Hebei Prov, Baoding 071002, Peoples R China
推荐引用方式 GB/T 7714	He, Cong,Liu, Ming,Xiong, Peng,et al. Localization of myocardial infarction using a multi-branch weight sharing network based on 2-D vectorcardiogram[J]. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE,2022,116:9.
APA	He, Cong.,Liu, Ming.,Xiong, Peng.,Yang, Jianli.,Du, Haiman.,...&Liu, Xiuling.(2022).Localization of myocardial infarction using a multi-branch weight sharing network based on 2-D vectorcardiogram.ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE,116,9.
MLA	He, Cong,et al."Localization of myocardial infarction using a multi-branch weight sharing network based on 2-D vectorcardiogram".ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 116(2022):9.