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Vascular Interventional Surgery Path Planning and 3D Visual Navigation
Received date: 2023-03-14
Accepted date: 2023-04-28
Online published: 2025-06-06
Fu Zeyu, Fu Zhuang, Guan Yisheng . Vascular Interventional Surgery Path Planning and 3D Visual Navigation[J]. Journal of Shanghai Jiaotong University(Science), 2025 , 30(3) : 472 -481 . DOI: 10.1007/s12204-023-2653-4
[1] The Writing Committee of the Report on Cardiovascular Health and Diseases in China. Report on cardiovascular health and diseases in China 2021: An updated summary [J]. Chinese Circulation Journal, 2022, 37(6): 553-578 (in Chinese).
[2] LEVY R I, JESSE M J, MOCK M B. Position on percutaneous transluminal coronary angioplasty (PTCA) [J]. Circulation, 1979, 59(3): 613.
[3] LOWE H C, OESTERLE S N, KHACHIGIAN L M. Coronary in-stent restenosis: Current status and future strategies [J]. Journal of the American College of Cardiology, 2002, 39(2): 183-193.
[4] KIRIŞLI H A, SCHAAP M, METZ C T, et al. Standardized evaluation framework for evaluating coronary artery stenosis detection, stenosis quantification and lumen segmentation algorithms in computed tomography angiography [J]. Medical Image Analysis, 2013, 17(8): 859-876.
[5] LESSARD S, LAU C, CHAV R, et al. Guidewire tracking during endovascular neurosurgery [J]. Medical Engineering & Physics, 2010, 32(8): 813-821.
[6] GAO M K, CHEN Y M, ZHANG D H, et al. Path planning of vascular access surgery based on improved ant colony algorithm [J]. Journal of Shanghai University (Natural Science Edition), 2019, 25(2): 198-205 (in Chinese).
[7] AZIZI A, TREMBLAY C, MARTEL S. Trajectory planning for vascular navigation from 3D angiography images and vessel centerline data [C]//2017 International Conference on Manipulation, Automation and Robotics at Small Scales. Montreal: IEEE, 2017: 1-6.
[8] GUO J, SUN Y, GUO S X. A training system for vascular interventional surgeons based on local path planning [C]//2021 IEEE International Conference on Mechatronics and Automation. Takamatsu: IEEE, 2021: 1328-1333.
[9] FU Z Y, FU Z, LU C Z, et al. Robust implementation of foreground extraction and vessel segmentation for X-ray coronary angiography image sequence [DB/OL]. (2022-09-15). https://arxiv.org/abs/2209.07237
[10] ZHUANG Y, CHEN G B, FU Z. Segmentation and diagnosis of angiocardiography image [J]. Machinery & Electronics, 2018, 36(4): 16-19, 37 (in Chinese).
[11] SUI C X, FU Z, FU Z Y, et al. A novel method for vessel segmentation and automatic diagnosis of vascular stenosis [C]//2019 IEEE International Conference on Robotics and Biomimetics. Dali: IEEE, 2019: 918-923.
[12] CHERKASSKY B V, GOLDBERG A V, RADZIK T. Shortest paths algorithms: Theory and experimental evaluation [J]. Mathematical Programming, 1996, 73(2): 129-174.
[13] FANG H H, ZHU J J, AI D N, et al. Greedy soft matching for vascular tracking of coronary angiographic image sequences [J]. IEEE Transactions on Circuits and Systems for Video Technology, 2020, 30(5): 1466-1480.
[14] ÇIMEN S, GOOYA A, GRASS M, et al. Reconstruction of coronary arteries from X-ray angiography: A review [J]. Medical Image Analysis, 2016, 32: 46-68.
[15] BANERJEE A, GALASSI F, ZACUR E, et al. Point-cloud method for automated 3D coronary tree reconstruction from multiple non-simultaneous angiographic projections [J]. IEEE Transactions on Medical Imaging, 2019, 39(4): 1278-1290.
[16] JIA Y S, XIAO D Q, YAN Q, et al. A method for reconstructing 3D skeleton of coronary artery from 2D X-ray angiographic images [C]//IMIP 2022: 2022 4th International Conference on Intelligent Medicine and Image Processing. Tianjin: ACM, 2022: 70-75.
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