A Unified Framework for Multi-Guidewire Endpoint Localization in Fluoroscopy Images

doi:10.1109/TBME.2021.3118001

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

	A Unified Framework for Multi-Guidewire Endpoint Localization in Fluoroscopy Images
	Li, Rui-Qi 3,4; Xie, Xiao-Liang 3,4; Zhou, Xiao-Hu 3,4; Liu, Shi-Qi 3,4; Ni, Zhen-Liang 3,4; Zhou, Yan-Jie 3,4; Bian, Gui-Bin 3,4; Hou, Zeng-Guang 1,2,4
刊名	IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
	2022-04-01
卷号	69 期号:4 页码:1406-1416
关键词	Location awareness Surgery Instruments Feature extraction Task analysis Proposals Measurement Guidewire endpoint keypoint localization surgical instrument
ISSN号	0018-9294
DOI	10.1109/TBME.2021.3118001
通讯作者	Zhou, Xiao-Hu(zhouxiaohu2014@ia.ac.cn) ; Hou, Zeng-Guang(zengguang.hou@ia.ac.cn)
英文摘要	Objective: In this paper, Keypoint Localization Region-based CNN (KL R-CNN) is proposed, which can simultaneously accomplish the guidewire detection and endpoint localization in a unified model. Methods: KL R-CNN modifies Mask R-CNN by replacing the mask branch with a novel keypoint localization branch. Besides, some settings of Mask R-CNN are also modified to generate the keypoint localization results at a higher detail level. At the same time, based on the existing metrics of Average Precision (AP) and Percentage of Correct Keypoints (PCK), a new metric named AP(PCK) is proposed to evaluate the overall performance on the multi-guidewire endpoint localization task. Compared with existing metrics, AP(PCK) is easy to use and its results are more intuitive. Results: Compared with existing methods, KL R-CNN has better performance when the threshold is loose, reaching a mean AP(PCK) of 90.65% when the threshold is 9 pixels. Conclusion: KL R-CNN achieves the state-of-the-art performance on the multi-guidewire endpoint localization task and has application potentials. Significance: KL R-CNN can achieve the localization of guidewire endpoints in fluoroscopy images, which is a prerequisite for computer-assisted percutaneous coronary intervention. KL R-CNN can also be extended to other multi-instrument localization tasks.
资助项目	National Natural Science Foundation of China[62073325] ; National Natural Science Foundation of China[62003343] ; National Natural Science Foundation of China[U1913601] ; National Natural Science Foundation of China[U20A20224] ; National Key Research and Development Program of China[2019YFB1311700] ; Youth Innovation Promotion Association of CAS[2020140] ; Strategic Priority Research Program of CAS[XDB32040000]
WOS研究方向	Engineering
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000792917400018
资助机构	National Natural Science Foundation of China ; National Key Research and Development Program of China ; Youth Innovation Promotion Association of CAS ; Strategic Priority Research Program of CAS
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/49392]
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	Zhou, Xiao-Hu; Hou, Zeng-Guang
作者单位	1.Macau Univ Sci & Technol, Inst Syst Engn, CAS Must Joint Lab Intelligence Sci & Technol, Macau 999078, Peoples R China 2.CAS Ctr Excellence Brain Sci & Technol, Beijing 100190, Peoples R China 3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 4.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Li, Rui-Qi,Xie, Xiao-Liang,Zhou, Xiao-Hu,et al. A Unified Framework for Multi-Guidewire Endpoint Localization in Fluoroscopy Images[J]. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING,2022,69(4):1406-1416.
APA	Li, Rui-Qi.,Xie, Xiao-Liang.,Zhou, Xiao-Hu.,Liu, Shi-Qi.,Ni, Zhen-Liang.,...&Hou, Zeng-Guang.(2022).A Unified Framework for Multi-Guidewire Endpoint Localization in Fluoroscopy Images.IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING,69(4),1406-1416.
MLA	Li, Rui-Qi,et al."A Unified Framework for Multi-Guidewire Endpoint Localization in Fluoroscopy Images".IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING 69.4(2022):1406-1416.