{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T11:44:59Z","timestamp":1777895099528,"version":"3.51.4"},"reference-count":45,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Biomedical Signal Processing and Control"],"published-print":{"date-parts":[[2026,7]]},"DOI":"10.1016\/j.bspc.2026.110012","type":"journal-article","created":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T04:18:31Z","timestamp":1772857111000},"page":"110012","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PA","title":["A Path-Selectable Image-Based method for precise vascular morphological measurement in Robot-Assisted endovascular surgery"],"prefix":"10.1016","volume":"120","author":[{"given":"Renfei","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Linjie","family":"Dong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6649-1485","authenticated-orcid":false,"given":"Xingsong","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4653-8848","authenticated-orcid":false,"given":"Mengqian","family":"Tian","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haobo","family":"Su","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.bspc.2026.110012_b0005","doi-asserted-by":"crossref","DOI":"10.1126\/sciadv.abm2456","article-title":"Multiscale topology characterizes dynamic tumor vascular networks","volume":"8","author":"Stolz","year":"2022","journal-title":"Sci. Adv."},{"key":"10.1016\/j.bspc.2026.110012_b0010","doi-asserted-by":"crossref","unstructured":"L. Meng, M. Jiang, C. Zhang, J. Zhang, Deep learning segmentation, classification, and risk prediction of complex vascular lesions on intravascular ultrasound images, Biomed. Signal Process. Control 82 (2023) 104584.https:\/\/ doi.org\/10.1016\/j.bspc.2023.104584.","DOI":"10.1016\/j.bspc.2023.104584"},{"key":"10.1016\/j.bspc.2026.110012_b0015","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2023.105539","article-title":"Optimization of retinal artery\/vein classification based on vascular topology","volume":"88","author":"Zhao","year":"2024","journal-title":"Biomed. Signal Process. Control"},{"key":"10.1016\/j.bspc.2026.110012_b0020","doi-asserted-by":"crossref","unstructured":"J. Ehling, B. Theek, F. Gremse, S. Baetke, D. M\u00f6ckel, J. Maynard, S.-A. Ricketts, H. Gr\u00fcll, M. Neeman, R. Knuechel, W. Lederle, F. Kiessling, T. Lammers, Micro-CT Imaging of Tumor Angiogenesis: Quantitative Measures Describing Micromorphology and Vascularization, Am. J. Pathol. 184 (2014) 431\u2013441.https:\/\/doi.org\/10.1016\/j.ajpath.2013. 10.014.","DOI":"10.1016\/j.ajpath.2013.10.014"},{"key":"10.1016\/j.bspc.2026.110012_b0025","doi-asserted-by":"crossref","first-page":"1232","DOI":"10.1016\/j.acra.2005.05.027","article-title":"Vessel Tortuosity and Brain Tumor Malignancy: a Blinded Study1","volume":"12","author":"Bullitt","year":"2005","journal-title":"Acad. Radiol."},{"key":"10.1016\/j.bspc.2026.110012_b0030","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2024.106991","article-title":"SDLU-Net: a similarity-based dynamic linking network for the automated segmentation of abdominal aorta aneurysms and branching vessels","volume":"100","author":"Zhang","year":"2025","journal-title":"Biomed. Signal Process. Control"},{"key":"10.1016\/j.bspc.2026.110012_b0035","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1593\/neo.131848","article-title":"Multispectral Fluorescence Ultramicroscopy: Three-Dimensional Visualization and Automatic Quantification of Tumor Morphology, Drug Penetration, and Antiangiogenic Treatment Response","volume":"16","author":"Dobosz","year":"2014","journal-title":"Neoplasia"},{"key":"10.1016\/j.bspc.2026.110012_b0040","doi-asserted-by":"crossref","first-page":"3352","DOI":"10.1364\/BOE.425512","article-title":"Characterization and quantification of necrotic tissues and morphology in multicellular ovarian cancer tumor spheroids using optical coherence tomography","volume":"12","author":"Yan","year":"2021","journal-title":"Biomed. Opt. Express"},{"key":"10.1016\/j.bspc.2026.110012_b0045","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1038\/hr.2016.145","article-title":"Vascular structural and functional changes: their association with causality in hypertension: models, remodeling and relevance","volume":"40","author":"Lee","year":"2017","journal-title":"Hypertens. Res."},{"key":"10.1016\/j.bspc.2026.110012_b0050","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/j.ijcard.2021.08.036","article-title":"Impact of vascular morphology and plaque characteristics on computed tomography derived fractional flow reserve in early stage coronary artery disease","volume":"343","author":"Tsugu","year":"2021","journal-title":"Int. J. Cardiol."},{"key":"10.1016\/j.bspc.2026.110012_b0055","doi-asserted-by":"crossref","unstructured":"Y. Zhou, M. Xu, Y. Hu, H. Lin, J. Jacob, P.A. Keane, D.C. Alexander, Learning to Address Intra-segment Misclassification in Retinal Imaging, in: M. de Bruijne, P.C. Cattin, S. Cotin, N. Padoy, S. Speidel, Y. Zheng, C. Essert (Eds.), Med. Image Comput. Comput. Assist. Interv. \u2013 MICCAI 2021, Springer International Publishing, Cham, 2021: pp. 482\u2013492.https:\/\/doi.org\/10.1007\/978-3-030-87193-2_46.","DOI":"10.1007\/978-3-030-87193-2_46"},{"key":"10.1016\/j.bspc.2026.110012_b0060","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1167\/tvst.9.2.6","article-title":"Insights into Systemic Disease through Retinal Imaging-based Oculomics","volume":"9","author":"Wagner","year":"2020","journal-title":"Transl. Vis. Sci. Technol."},{"key":"10.1016\/j.bspc.2026.110012_b0065","first-page":"38","article-title":"Measurement and characterization of retinal vascular morphology parameters based on artificial intelligence automated analysis technology","volume":"42","author":"Shi","year":"2024","journal-title":"Chin. J. Exp. Ophthalmol."},{"key":"10.1016\/j.bspc.2026.110012_b0070","doi-asserted-by":"crossref","first-page":"498","DOI":"10.1038\/s41551-020-00626-4","article-title":"A deep-learning system for the assessment of cardiovascular disease risk via the measurement of retinal-vessel calibre","volume":"5","author":"Cheung","year":"2021","journal-title":"Nat. Biomed. Eng."},{"key":"10.1016\/j.bspc.2026.110012_b0075","doi-asserted-by":"crossref","DOI":"10.1002\/pul2.12035","article-title":"Retinal vessel changes in pulmonary arterial hypertension","volume":"12","author":"DuPont","year":"2022","journal-title":"Pulm. Circ."},{"key":"10.1016\/j.bspc.2026.110012_b0080","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1038\/s41433-020-01233-y","article-title":"Optical coherence tomography angiography in diabetic retinopathy: an updated review","volume":"35","author":"Sun","year":"2021","journal-title":"Eye"},{"key":"10.1016\/j.bspc.2026.110012_b0085","doi-asserted-by":"crossref","unstructured":"G.P. P, B. Biswal, P.K. Biswal, Robust classification of neovascularization using random forest classifier via convoluted vascular network, Biomed. Signal Process. Control 66 (2021) 102420.https:\/\/doi.org\/10.1016\/j.bspc.2021.102420.","DOI":"10.1016\/j.bspc.2021.102420"},{"key":"10.1016\/j.bspc.2026.110012_b0090","doi-asserted-by":"crossref","DOI":"10.1117\/1.JMI.11.2.024002","article-title":"Systematic evaluation of MRI-based characterization of tumor-associated vascular morphology and hemodynamics via a dynamic digital phantom","volume":"11","author":"Wu","year":"2024","journal-title":"J. Med. Imaging"},{"key":"10.1016\/j.bspc.2026.110012_b0095","article-title":"A semi-automatic cardiovascular annotation and quantification toolbox utilizing prior knowledge-guided feature learning","author":"Zhang","year":"2025","journal-title":"Biomed. Signal Process. Control 102"},{"key":"10.1016\/j.bspc.2026.110012_b0100","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1167\/tvst.11.7.12","article-title":"AutoMorph: Automated Retinal Vascular Morphology Quantification Via a Deep Learning Pipeline","volume":"11","author":"Zhou","year":"2022","journal-title":"Transl. Vis. Sci. Technol."},{"key":"10.1016\/j.bspc.2026.110012_b0105","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1111\/j.1549-8719.2010.00075.x","article-title":"Multifractal and Lacunarity Analysis of Microvascular Morphology and Remodeling","volume":"18","author":"Gould","year":"2011","journal-title":"Microcirculation"},{"key":"10.1016\/j.bspc.2026.110012_b0110","doi-asserted-by":"crossref","unstructured":"F.N. Rahaghi, P. Nardelli, E. Harder, I. Singh, G.V. S\u00e1nchez-Ferrero, J.C. Ross, R. San Jos\u00e9 Est\u00e9par, S.Y. Ash, A.R. Hunsaker, B.A. Maron, J.A. Leopold, A.B. Waxman, R. San Jos\u00e9 Est\u00e9par, G.R. Washko, Quantification of Arterial and Venous Morphologic Markers in Pulmonary Arterial Hypertension Using CT Imaging, Chest 160 (2021) 2220\u20132231.https:\/\/doi.org\/10.1016\/j.chest.2021.%252006.069.","DOI":"10.1016\/j.chest.2021.06.069"},{"key":"10.1016\/j.bspc.2026.110012_b0115","doi-asserted-by":"crossref","first-page":"1071","DOI":"10.1007\/s11831-016-9199-7","article-title":"Computational Modeling of Tumor-Induced Angiogenesis","volume":"24","author":"Vilanova","year":"2017","journal-title":"Arch. Comput. Methods Eng."},{"key":"10.1016\/j.bspc.2026.110012_b0120","doi-asserted-by":"crossref","first-page":"2532","DOI":"10.1093\/humrep\/deac202","article-title":"Assessment of first-trimester utero-placental vascular morphology by 3D power Doppler ultrasound image analysis using a skeletonization algorithm: the Rotterdam Periconception Cohort","volume":"37","author":"De Vos","year":"2022","journal-title":"Hum. Reprod."},{"key":"10.1016\/j.bspc.2026.110012_b0125","doi-asserted-by":"crossref","first-page":"4577","DOI":"10.3390\/jcm13154577","article-title":"Machine Learning and Statistical Shape Modelling Methodologies to Assess Vascular Morphology before and after Aortic Valve Replacement","volume":"13","author":"Aljassam","year":"2024","journal-title":"J. Clin. Med."},{"key":"10.1016\/j.bspc.2026.110012_b0130","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.aopr.2023.05.002","article-title":"Quantification of vascular morphology in optical coherence tomography angiography in primary open angle glaucoma","volume":"3","author":"Kalva","year":"2023","journal-title":"Adv. Ophthalmol. Pract. Res."},{"key":"10.1016\/j.bspc.2026.110012_b0135","doi-asserted-by":"crossref","first-page":"2617","DOI":"10.1177\/0271678X211010071","article-title":"Magnetic resonance imaging-based changes in vascular morphology and cerebral perfusion in subacute ischemic stroke","volume":"41","author":"Kufner","year":"2021","journal-title":"J. Cereb. Blood Flow Metab."},{"key":"10.1016\/j.bspc.2026.110012_b0140","doi-asserted-by":"crossref","DOI":"10.1002\/pul2.12223","article-title":"Automated quantification of the pulmonary vasculature in pulmonary embolism and chronic thromboembolic pulmonary hypertension","volume":"13","author":"Zhai","year":"2023","journal-title":"Pulm. Circ."},{"key":"10.1016\/j.bspc.2026.110012_b0145","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2020.101691","article-title":"San Jos\u00e9 Est\u00e9par, Generative-based airway and vessel morphology quantification on chest CT images","volume":"63","author":"Nardelli","year":"2020","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.bspc.2026.110012_b0150","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2023.104660","article-title":"Deep learning for anterior segment OCT angiography automated denoising and vascular quantitative measurement","volume":"83","author":"Luo","year":"2023","journal-title":"Biomed. Signal Process. Control"},{"key":"10.1016\/j.bspc.2026.110012_b0155","doi-asserted-by":"crossref","first-page":"1728","DOI":"10.1109\/TRO.2025.3543261","article-title":"Ultrasound Image-based Average Q-Learning Control of magnetic Microrobots","volume":"41","author":"Liu","year":"2025","journal-title":"IEEE Trans. Robot."},{"key":"10.1016\/j.bspc.2026.110012_b0160","doi-asserted-by":"crossref","first-page":"2306","DOI":"10.1109\/TRO.2024.3378442","article-title":"Xu, Design and Hierarchical Control of a Homocentric Variable-Stiffness magnetic Catheter for Multiarm Robotic Ultrasound-Assisted Coronary intervention","volume":"40","author":"Li","year":"2024","journal-title":"IEEE Trans. Robot."},{"key":"10.1016\/j.bspc.2026.110012_b0165","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1109\/TMRB.2023.3260273","article-title":"Real-Time Pose Tracking for a Continuum Guidewire Robot under Fluoroscopic Imaging","author":"Ravigopal","year":"2023","journal-title":"IEEE Trans. Med. Robot. Bionics 5"},{"key":"10.1016\/j.bspc.2026.110012_b0170","doi-asserted-by":"crossref","first-page":"1569","DOI":"10.1007\/s11548-024-03208-w","article-title":"Autonomous navigation of catheters and guidewires in mechanical thrombectomy using inverse reinforcement learning","volume":"19","author":"Robertshaw","year":"2024","journal-title":"Int. J. Comput. Assist. Radiol. Surg."},{"key":"10.1016\/j.bspc.2026.110012_b0175","doi-asserted-by":"crossref","unstructured":"T. Yao, B. Lu, M. Kowarschik, Y. Yuan, H. Zhao, S. Ourselin, K. Althoefer, J. Ge, P. Qi, Advancing Embodied Intelligence in Robotic-Assisted Endovascular Procedures: A Systematic Review of AI Solutions, IEEE Rev. Biomed. Eng. PP (2025).https:\/\/doi.org\/10.1109\/RBME.2025.3641383.","DOI":"10.1109\/RBME.2025.3641383"},{"key":"10.1016\/j.bspc.2026.110012_b0180","doi-asserted-by":"crossref","unstructured":"J. Sun, R. Tang, Q. Zhang, J. Liu, L. Gao, W. Yang, X. Chen, Y. Tang, Advancements and challenges in autonomous endovascular interventional robotics: A comprehensive review, iScience 28 (2025).https:\/\/doi.org\/10.1016\/j.isci. 2025.114024.","DOI":"10.1016\/j.isci.2025.114024"},{"key":"10.1016\/j.bspc.2026.110012_b0185","first-page":"333","article-title":"Cervical Spine Navigation and Enabled Robotics: a New Frontier in Minimally Invasive Surgery","volume":"17","author":"Lebl","year":"2021","journal-title":"HSS Journal\u00ae Musculoskelet. J. Hosp. Spec. Surg."},{"key":"10.1016\/j.bspc.2026.110012_b0190","doi-asserted-by":"crossref","first-page":"1789","DOI":"10.1007\/s00423-022-02465-0","article-title":"Robot-assisted techniques in vascular and endovascular surgery","volume":"407","author":"P\u00fcschel","year":"2022","journal-title":"Langenbecks Arch. Surg."},{"key":"10.1016\/j.bspc.2026.110012_b0195","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.isurg.2023.11.001","article-title":"Initial experience in the treatment of lower extremity arterial occlusive disease using a universal vascular interventional surgery robotic system","volume":"6","author":"Dai","year":"2023","journal-title":"Intell. Surg."},{"key":"10.1016\/j.bspc.2026.110012_b0200","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2023.107540","article-title":"Enhancing percutaneous coronary intervention with heuristic path planning and deep-learning-based vascular segmentation","volume":"166","author":"Yao","year":"2023","journal-title":"Comput. Biol. Med."},{"key":"10.1016\/j.bspc.2026.110012_b0205","doi-asserted-by":"crossref","first-page":"2769","DOI":"10.1109\/JSEN.2023.3334484","article-title":"A Vascular Shape Reconstruction Method based on Multicore FBG Sensing","volume":"24","author":"Zhang","year":"2024","journal-title":"IEEE Sens. J."},{"key":"10.1016\/j.bspc.2026.110012_b0210","doi-asserted-by":"crossref","first-page":"7413","DOI":"10.3390\/s24227413","article-title":"A Near-Infrared Imaging System for Robotic Venous Blood Collection","volume":"24","author":"Yang","year":"2024","journal-title":"Sensors"},{"key":"10.1016\/j.bspc.2026.110012_b0215","first-page":"1","article-title":"A Sensor-less Guider Contact Force Estimation Approach for Endovascular Slender Robot-Assisted Guidance System","volume":"74","author":"Zhang","year":"2025","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"10.1016\/j.bspc.2026.110012_b0220","doi-asserted-by":"crossref","first-page":"1015","DOI":"10.1089\/soro.2022.0179","article-title":"Design and Development of a Continuum Robot with Switching-Stiffness","volume":"10","author":"Shen","year":"2023","journal-title":"Soft Robot."},{"key":"10.1016\/j.bspc.2026.110012_b0225","doi-asserted-by":"crossref","first-page":"688","DOI":"10.1109\/TCST.2018.2884222","article-title":"Noncollocated Position Control of Tendon-Sheath Actuated Slender Manipulator","volume":"28","author":"Wang","year":"2020","journal-title":"IEEE Trans. Control Syst. Technol."}],"container-title":["Biomedical Signal Processing and Control"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1746809426005665?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1746809426005665?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T07:42:37Z","timestamp":1777621357000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1746809426005665"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":45,"alternative-id":["S1746809426005665"],"URL":"https:\/\/doi.org\/10.1016\/j.bspc.2026.110012","relation":{},"ISSN":["1746-8094"],"issn-type":[{"value":"1746-8094","type":"print"}],"subject":[],"published":{"date-parts":[[2026,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A Path-Selectable Image-Based method for precise vascular morphological measurement in Robot-Assisted endovascular surgery","name":"articletitle","label":"Article Title"},{"value":"Biomedical Signal Processing and Control","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.bspc.2026.110012","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"110012"}}