A Novel Spatial Position Prediction Navigation System Makes Surgery More Accurate

doi:10.1109/TMI.2023.3297188

	A Novel Spatial Position Prediction Navigation System Makes Surgery More Accurate
	Zhang, Lin-Sen 1,2; Liu, Shi-Qi2,3,4 ; Xie, Xiao-Liang2 ; Zhou, Xiao-Hu2 ; Hou, Zeng-Guang2,5,6,7 ; Wang, Chao-Nan 8; Qu, Xin-Kai 3; Han, Wen-Zheng 3,4; Ma, Xi-Yao 2,4; Song, Meng 2
发表期刊	IEEE TRANSACTIONS ON MEDICAL IMAGING
ISSN	0278-0062
	2023-12-01
卷号	42 期号:12 页码:3614-3624
通讯作者	Liu, Shi-Qi(shiqi.liu@ia.ac.cn) ; Hou, Zeng-Guang(zengguang.hou@ia.ac.cn)
摘要	During intravascular interventional surgery, the 3D surgical navigation system can provide doctors with 3D spatial information of the vascular lumen, reducing the impact of missing dimension caused by digital subtraction angiography (DSA) guidance and further improving the success rate of surgeries. Nevertheless, this task often comes with the challenge of complex registration problems due to vessel deformation caused by respiratory motion and high requirements for the surgical environment because of the dependence on external electromagnetic sensors. This article proposes a novel 3D spatial predictive positioning navigation (SPPN) technique to predict the real-time tip position of surgical instruments. In the first stage, we propose a trajectory prediction algorithm integrated with instrumental morphological constraints to generate the initial trajectory. Then, a novel hybrid physical model is designed to estimate the trajectory's energy and mechanics. In the second stage, a point cloud clustering algorithm applies multi-information fusion to generate the maximum probability endpoint cloud. Then, an energy-weighted probability density function is introduced using statistical analysis to achieve the prediction of the 3D spatial location of instrument endpoints. Extensive experiments are conducted on 3D-printed human artery and vein models based on a high-precision electromagnetic tracking system. Experimental results demonstrate the outstanding performance of our method, reaching 98.2% of the achievement ratio and less than 3 mm of the average positioning accuracy. This work is the first 3D surgical navigation algorithm that entirely relies on vascular interventional robot sensors, effectively improving the accuracy of interventional surgery and making it more accessible for primary surgeons.
关键词	Vascular interventional surgery 3D prediction guide autonomous operation path-planning weighted probability error ellipsoid
DOI	10.1109/TMI.2023.3297188
关键词[WOS]	CONTINUUM ROBOTS ; GUIDEWIRE ; SIMULATION ; DYNAMICS ; ROD ; INTERVENTION ; CURVATURE
收录类别	SCI
语种	英语
资助项目	National Key Research and Development Program of China
项目资助者	National Key Research and Development Program of China
WOS研究方向	Computer Science ; Engineering ; Imaging Science & Photographic Technology ; Radiology, Nuclear Medicine & Medical Imaging
WOS类目	Computer Science, Interdisciplinary Applications ; Engineering, Biomedical ; Engineering, Electrical & Electronic ; Imaging Science & Photographic Technology ; Radiology, Nuclear Medicine & Medical Imaging
WOS记录号	WOS:001122030500002
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/55001
专题	多模态人工智能系统全国重点实验室
通讯作者	Liu, Shi-Qi; Hou, Zeng-Guang
作者单位	1.Univ Sci & Technol Beijing, Inst Artificial Intelligence, Beijing 100083, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence S, Beijing 100190, Peoples R China 3.Fudan Univ, Dept Cardiol, Huadong Hosp, Shanghai 2000040, Peoples R China 4.Shanghai Key Lab Clin Geriatr Med, Shanghai 200040, Peoples R China 5.Univ Chinese Acad Sci, Sch ArtificialI Intelligence, Beijing 100049, Peoples R China 6.CAS Ctr Excellence Brain Sci & Intelligence Techno, Beijing 100190, Peoples R China 7.Macau Univ Sci & Technol, CASIA MUST Joint Lab Intelligence Sci & Technol, Inst Syst Engn, Macau 999078, Peoples R China 8.Chinese Acad Med Sci & Peking Union Med Coll, Plast Surg Hosp, Beijing 100144, Peoples R China
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Zhang, Lin-Sen,Liu, Shi-Qi,Xie, Xiao-Liang,et al. A Novel Spatial Position Prediction Navigation System Makes Surgery More Accurate[J]. IEEE TRANSACTIONS ON MEDICAL IMAGING,2023,42(12):3614-3624.
APA	Zhang, Lin-Sen.,Liu, Shi-Qi.,Xie, Xiao-Liang.,Zhou, Xiao-Hu.,Hou, Zeng-Guang.,...&Song, Meng.(2023).A Novel Spatial Position Prediction Navigation System Makes Surgery More Accurate.IEEE TRANSACTIONS ON MEDICAL IMAGING,42(12),3614-3624.
MLA	Zhang, Lin-Sen,et al."A Novel Spatial Position Prediction Navigation System Makes Surgery More Accurate".IEEE TRANSACTIONS ON MEDICAL IMAGING 42.12(2023):3614-3624.