An Interventionalist-Behavior-Based Data Fusion Framework for Guidewire Tracking in Percutaneous Coronary Intervention

doi:10.1109/TSMC.2018.2876465

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

	An Interventionalist-Behavior-Based Data Fusion Framework for Guidewire Tracking in Percutaneous Coronary Intervention
	Zhou, Xiao-Hu 2,3; Bian, Gui-Bin 2; Xie, Xiao-Liang 2; Hou, Zeng-Guang 1,2,3
刊名	IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
	2020-11-01
卷号	50 期号:11 页码:4836-4849
关键词	Tracking Sensors Tools Catheters Electromyography Data integration Frequency modulation Data fusion framework guidewire tracking interventionalist behavior percutaneous coronary intervention (PCI)
ISSN号	2168-2216
DOI	10.1109/TSMC.2018.2876465
通讯作者	Hou, Zeng-Guang(zengguang.hou@ia.ac.cn)
英文摘要	Guidewire tracking is a clinical challenge in percutaneous coronary intervention (PCI). The current practice of image-based and sensor-based tracking techniques is still limited by radiation exposure, contrast injection, device sterilization, and procedure safety. In this paper, an interventionalist-behavior-based data fusion framework is developed to provide a novel strategy for tracking guidewire motions in PCI. Four types of natural behavior were acquired from ten interventionalists while performing guidewire translation and rotation based on a simulation platform. Different numbers of behaviors are fused by a hierarchical framework with six local tracking models and three ensemble algorithms. After Gaussian mixture regression-based ensemble fusion, a three-behavior scheme can achieve average tracking errors of 1.07 +/- 0.17 mm for guidewire translation, and 20.05 +/- 3.36 degrees for guidewire rotation. Relevant statistical analysis further reveals that this scheme outperforms the cases using fewer behaviors, and ensemble fusion brings significant error reduction compared with only local fusion. These meaningful results indicate the great potential of the proposed framework for promoting the improvement of guidewire tracking in PCI.
资助项目	National Natural Science Foundation of China[61533016] ; National Natural Science Foundation of China[61720106012] ; National Natural Science Foundation of China[61611130217] ; National Natural Science Foundation of China[61603386] ; National Natural Science Foundation of China[61421004] ; Strategic Priority Research Program of CAS[XDBS01040100] ; Beijing Natural Science Foundation[L172050]
WOS关键词	SURFACE ELECTROMYOGRAPHY ; ENDOVASCULAR SURGERY ; NAVIGATION ; CATHETERS ; DISPLAY ; SENSOR
WOS研究方向	Automation & Control Systems ; Computer Science
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000578826300078
资助机构	National Natural Science Foundation of China ; Strategic Priority Research Program of CAS ; Beijing Natural Science Foundation
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/42134]
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	Hou, Zeng-Guang
作者单位	1.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Beijing 100190, Peoples R China 2.Chinese Acad Sci, State Key Lab Management & Control Complex Syst, Inst Automat, Beijing 100190, Peoples R China 3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Zhou, Xiao-Hu,Bian, Gui-Bin,Xie, Xiao-Liang,et al. An Interventionalist-Behavior-Based Data Fusion Framework for Guidewire Tracking in Percutaneous Coronary Intervention[J]. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,2020,50(11):4836-4849.
APA	Zhou, Xiao-Hu,Bian, Gui-Bin,Xie, Xiao-Liang,&Hou, Zeng-Guang.(2020).An Interventionalist-Behavior-Based Data Fusion Framework for Guidewire Tracking in Percutaneous Coronary Intervention.IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,50(11),4836-4849.
MLA	Zhou, Xiao-Hu,et al."An Interventionalist-Behavior-Based Data Fusion Framework for Guidewire Tracking in Percutaneous Coronary Intervention".IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 50.11(2020):4836-4849.