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A Real-Time Multifunctional Framework for Guidewire Morphological and Positional Analysis in Interventional X-Ray Fluoroscopy

文献类型：期刊论文

作者Zhou, Yan-Jie1,2; Xie, Xiao-Liang1; Zhou, Xiao-Hu1; Liu, Shi-Qi1; Bian, Gui-Bin1; Hou, Zeng-Guang1,2,3
刊名IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS
出版日期2021-09-01
卷号13期号:3页码:657-667
关键词Deep learning guidewire robot-assisted intervention segmentation and localization X-ray fluoroscopy
ISSN号2379-8920
DOI10.1109/TCDS.2020.3023952
通讯作者Hou, Zeng-Guang(zengguang.hou@ia.ac.cn)
英文摘要In endovascular and cardiovascular surgery, real-time guidewire morphological and positional analysis is an important prerequisite for robot-assisted intervention, which can aid in reducing the radiation dose, contrast agent, and procedure time. Nevertheless, this task often comes with the challenge of the deformable elongated structure with low contrast in noisy X-ray fluoroscopy. In this article, a real-time multifunctional framework is proposed for fully automatic guidewire morphological and positional analysis, namely, guidewire segmentation, endpoint localization, and angle measurement. In the first stage, the proposed fast attention recurrent network (FAR-Net) achieves real-time and accurate guidewire segmentation. In the second stage, the endpoint localization and angle measurement algorithm robustly obtain subpixel-level endpoint and angle of the guidewire tip. Quantitative and qualitative evaluations on the MSGSeg data set consisting of 180 X-ray sequences from 30 patients demonstrate that the proposed framework significantly outperforms simpler baselines as well as the best previously published result for this task. The proposed approach reached F-1-Score of 0.938, mean distance error of 0.596 pixels, endpoint localization and angle measurement accuracy of 97.8% and 95.3%, and an inference rate of approximately 13 FPS. The proposed framework not only addresses the issues of extreme class imbalance and misclassified examples but also meets the real-time requirements, achieving state-of-the-art performance. The proposed approach is promising for integration into robotic navigation frameworks to various intravascular applications, enabling robotic-assisted intervention.
WOS关键词WIRE TRACKING ; SEGMENTATION
资助项目National Key Research and Development Program of China[2019YFB1311700] ; National Natural Science Foundation of China[U1913210] ; National Natural Science Foundation of China[U1613210] ; National Natural Science Foundation of China[61533016] ; National Natural Science Foundation of China[62003343] ; Youth Innovation Promotion Association of Chinese Academy of Science[2020140] ; Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences[2018-I2M-AI-004] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDB32040000]
WOS研究方向Computer Science ; Robotics ; Neurosciences & Neurology
语种英语
WOS记录号WOS:000694697900024
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
资助机构National Key Research and Development Program of China ; National Natural Science Foundation of China ; Youth Innovation Promotion Association of Chinese Academy of Science ; Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences ; Strategic Priority Research Program of Chinese Academy of Sciences
源URL[http://ir.ia.ac.cn/handle/173211/46025]  
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, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
3.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Zhou, Yan-Jie,Xie, Xiao-Liang,Zhou, Xiao-Hu,et al. A Real-Time Multifunctional Framework for Guidewire Morphological and Positional Analysis in Interventional X-Ray Fluoroscopy[J]. IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS,2021,13(3):657-667.
APA Zhou, Yan-Jie,Xie, Xiao-Liang,Zhou, Xiao-Hu,Liu, Shi-Qi,Bian, Gui-Bin,&Hou, Zeng-Guang.(2021).A Real-Time Multifunctional Framework for Guidewire Morphological and Positional Analysis in Interventional X-Ray Fluoroscopy.IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS,13(3),657-667.
MLA Zhou, Yan-Jie,et al."A Real-Time Multifunctional Framework for Guidewire Morphological and Positional Analysis in Interventional X-Ray Fluoroscopy".IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS 13.3(2021):657-667.

入库方式： OAI收割

来源：自动化研究所

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