{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T22:56:15Z","timestamp":1792623375452,"version":"4.5.0"},"reference-count":46,"publisher":"Association for Research in Vision and Ophthalmology (ARVO)","issue":"1","license":[{"start":{"date-parts":[[2023,1,17]],"date-time":"2023-01-17T00:00:00Z","timestamp":1673913600000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Trans. Vis. Sci. Tech."],"published-print":{"date-parts":[[2023,1,17]]},"DOI":"10.1167\/tvst.12.1.20","type":"journal-article","created":{"date-parts":[[2023,1,17]],"date-time":"2023-01-17T15:31:05Z","timestamp":1673969465000},"page":"20","source":"Crossref","is-referenced-by-count":16,"title":["Vitreoretinal Surgical Instrument Tracking in Three Dimensions Using Deep Learning"],"prefix":"10.1167","volume":"12","author":[{"given":"Pierre F.","family":"Baldi","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of California, Irvine, CA, USA"},{"name":"Institute for Genomics and Bioinformatics, University of California, Irvine, CA, USA"},{"name":"Department of Biomedical Engineering, University of California, Irvine, CA, USA"},{"name":"Center for Translational Vision Research, Department of Ophthalmology, University of California, Irvine, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sherif","family":"Abdelkarim","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of California, Irvine, CA, USA"},{"name":"Institute for Genomics and Bioinformatics, University of California, Irvine, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junze","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of California, Irvine, CA, USA"},{"name":"Institute for Genomics and Bioinformatics, University of California, Irvine, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Josiah K.","family":"To","sequence":"additional","affiliation":[{"name":"Center for Translational Vision Research, Department of Ophthalmology, University of California, Irvine, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marialejandra Diaz","family":"Ibarra","sequence":"additional","affiliation":[{"name":"Gavin Herbert Eye Institute, Department of Ophthalmology, University of California, Irvine, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew W.","family":"Browne","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, University of California, Irvine, CA, USA"},{"name":"Center for Translational Vision Research, Department of Ophthalmology, University of California, Irvine, CA, USA"},{"name":"Gavin Herbert Eye Institute, Department of Ophthalmology, University of California, Irvine, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"27","reference":[{"issue":"7","key":"bib1","doi-asserted-by":"publisher","first-page":"645","DOI":"10.1016\/j.oret.2018.01.006","article-title":"Real-world outcomes of anti-vascular endothelial growth factor therapy in neovascular age-related macular degeneration in the United States","volume":"2","author":"Ciulla","year":"2018","journal-title":"Ophthalmol Retina"},{"key":"bib2","doi-asserted-by":"publisher","first-page":"279","DOI":"10.2147\/OPTH.S269162","article-title":"Ten-year real-world outcomes of anti-vascular endothelial growth factor therapy in neovascular age-related macular degeneration","volume":"15","author":"Cheema","year":"2021","journal-title":"Clin Ophthalmol"},{"issue":"2","key":"bib3","doi-asserted-by":"publisher","first-page":"132","DOI":"10.1111\/aos.v98.2","article-title":"Real-world 10-year experiences with intravitreal treatment with ranibizumab and aflibercept for neovascular age-related macular degeneration","volume":"98","author":"Brynskov","year":"2020","journal-title":"Acta Ophthalmol"},{"issue":"2","key":"bib4","doi-asserted-by":"publisher","first-page":"180","DOI":"10.1097\/SLA.0b013e318176bf4b","article-title":"Bias in surgical research","volume":"248","author":"Paradis","year":"2008","journal-title":"Ann Surg"},{"issue":"1","key":"bib5","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1080\/24699322.2021.1937320","article-title":"Challenges in surgical video annotation","volume":"26","author":"Ward","year":"2021","journal-title":"Comput Assist Surg (Abingdon)"},{"issue":"22","key":"bib6","doi-asserted-by":"publisher","first-page":"2368","DOI":"10.1001\/jama.2016.17217","article-title":"Translating artificial intelligence into clinical care","volume":"316","author":"Beam","year":"2016","journal-title":"JAMA"},{"issue":"4","key":"bib7","doi-asserted-by":"publisher","first-page":"483","DOI":"10.1057\/jors.2012.71","article-title":"Matching patient and physician preferences in designing a primary care facility network","volume":"65","author":"G\u00fcnes","year":"2014","journal-title":"J Oper Res Soc"},{"issue":"22","key":"bib8","doi-asserted-by":"publisher","first-page":"2402","DOI":"10.1001\/jama.2016.17216","article-title":"Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs","volume":"316","author":"Gulshan","year":"2016","journal-title":"JAMA"},{"issue":"3","key":"bib9","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1208\/s12248-018-0210-0","article-title":"Deep learning for drug design: an artificial intelligence paradigm for drug discovery in the big data era","volume":"20","author":"Jing","year":"2018","journal-title":"AAPS J"},{"issue":"7639","key":"bib10","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1038\/nature21056","article-title":"Dermatologist-level classification of skin cancer with deep neural networks","volume":"542","author":"Esteva","year":"2017","journal-title":"Nature"},{"key":"bib11","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1016\/j.neunet.2014.09.003","article-title":"Deep learning in neural networks: an overview","volume":"61","author":"Schmidhuber","year":"2015","journal-title":"Neural Netw"},{"issue":"4","key":"bib13","doi-asserted-by":"publisher","first-page":"1069","DOI":"10.1053\/j.gastro.2018.06.037","article-title":"Deep learning localizes and identifies polyps in real time with 96% accuracy in screening colonoscopy","volume":"155","author":"Urban","year":"2018","journal-title":"Gastroenterology"},{"issue":"7","key":"bib14","doi-asserted-by":"publisher","first-page":"1201","DOI":"10.3174\/ajnr.A5667","article-title":"Deep-learning convolutional neural networks accurately classify genetic mutations in gliomas","volume":"39","author":"Chang","year":"2018","journal-title":"AJNR Am J Neuroradiol"},{"issue":"5","key":"bib15","doi-asserted-by":"publisher","first-page":"1172","DOI":"10.1109\/TMI.2017.2655486","article-title":"Detecting cardiovascular disease from mammograms with deep learning","volume":"36","author":"Wang","year":"2017","journal-title":"IEEE Trans Med Imaging"},{"key":"bib16","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1016\/j.compbiomed.2017.03.024","article-title":"A multi-resolution approach for spinal metastasis detection using deep Siamese neural networks","volume":"84","author":"Wang","year":"2017","journal-title":"Comput Biol Med"},{"key":"bib17","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1002\/lsm.v53.1","article-title":"Combining deep learning with optical coherence tomography imaging to determine scalp hair and follicle counts","volume":"53","author":"Urban","year":"2021","journal-title":"Lasers Surg Med"},{"issue":"3","key":"bib18","doi-asserted-by":"publisher","first-page":"402","DOI":"10.1162\/neco.1993.5.3.402","article-title":"Neural networks for fingerprint recognition","volume":"5","author":"Baldi","year":"1993","journal-title":"Neural Comput"},{"issue":"3","key":"bib19","doi-asserted-by":"publisher","first-page":"1029","DOI":"10.1109\/TCBB.8857","article-title":"Deep learning for drug discovery and cancer research: automated analysis of vascularization images","volume":"16","author":"Urban","year":"2019","journal-title":"IEEE\/ACM Trans Comput Biol Bioinform"},{"issue":"12","key":"bib20","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1167\/tvst.10.12.30","article-title":"Deep learning-assisted multiphoton microscopy to reduce light exposure and expedite imaging in tissues with high and low light sensitivity","volume":"10","author":"McAleer","year":"2021","journal-title":"Transl Vis Sci Technol"},{"issue":"4","key":"bib21","doi-asserted-by":"publisher","first-page":"e0265185","DOI":"10.1371\/journal.pone.0265185","article-title":"Deep learning to enable color vision in the dark","volume":"17","author":"Browne","year":"2022","journal-title":"PLoS One"},{"issue":"15","key":"bib22","doi-asserted-by":"publisher","first-page":"3492","DOI":"10.1158\/1078-0432.CCR-18-0385","article-title":"Data analysis strategies in medical imaging","volume":"24","author":"Parmar","year":"2018","journal-title":"Clin Cancer Res"},{"issue":"4","key":"bib23","doi-asserted-by":"publisher","first-page":"224","DOI":"10.1016\/j.ogla.2019.03.008","article-title":"Validation of a deep learning model to screen for glaucoma using images from different fundus cameras and data augmentation","volume":"2","author":"Asaoka","year":"2019","journal-title":"Ophthalmol Glaucoma"},{"issue":"12","key":"bib24","doi-asserted-by":"publisher","first-page":"1627","DOI":"10.1016\/j.ophtha.2019.07.024","article-title":"Deep learning and glaucoma specialists: the relative importance of optic disc features to predict glaucoma referral in fundus photographs","volume":"126","author":"Phene","year":"2019","journal-title":"Ophthalmology"},{"key":"bib25","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1038\/s41746-018-0040-6","article-title":"Pivotal trial of an autonomous AI-based diagnostic system for detection of diabetic retinopathy in primary care offices","volume":"1","author":"Abr\u00e0moff","year":"2018","journal-title":"NPJ Digit Med"},{"issue":"1","key":"bib26","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1038\/s42003-019-0730-x","article-title":"Deep learning for detecting retinal detachment and discerning macular status using ultra-widefield fundus images","volume":"3","author":"Li","year":"2020","journal-title":"Commun Biol"},{"issue":"4","key":"bib27","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1167\/tvst.11.4.6","article-title":"Predicting visual improvement after macular hole surgery: a combined model using deep learning and clinical features","volume":"11","author":"Lachance","year":"2022","journal-title":"Transl Vis Sci Technol"},{"issue":"3","key":"bib28","doi-asserted-by":"publisher","first-page":"158","DOI":"10.1038\/s41551-018-0195-0","article-title":"Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning","volume":"2","author":"Poplin","year":"2018","journal-title":"Nat Biomed Eng"},{"issue":"3","key":"bib29","first-page":"158","article-title":"Retinal age gap as a predictive biomarker for mortality risk","volume":"2","author":"Zhu","year":"2022","journal-title":"Br J Ophthalmol"},{"issue":"4","key":"bib30","doi-asserted-by":"publisher","first-page":"684","DOI":"10.1097\/SLA.0000000000004425","article-title":"Machine learning for surgical phase recognition: a systematic review","volume":"273","author":"Garrow","year":"2021","journal-title":"Ann Surg"},{"issue":"1","key":"bib31","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1177\/00031348221101490","article-title":"Deep learning applications in surgery: Current uses and future directions.","volume":"89","author":"Morris","year":"2023","journal-title":"Am Surg."},{"issue":"4","key":"bib32","doi-asserted-by":"publisher","first-page":"649","DOI":"10.1097\/ALN.0000000000002186","article-title":"Development and validation of a deep neural network model for prediction of postoperative in-hospital mortality","volume":"129","author":"Lee","year":"2018","journal-title":"Anesthesiology"},{"issue":"2","key":"bib33","doi-asserted-by":"publisher","first-page":"170","DOI":"10.1001\/jamaophthalmol.2021.5742","article-title":"Evaluation of artificial intelligence-based intraoperative guidance tools for phacoemulsification cataract surgery","volume":"140","author":"Garcia Nespolo","year":"2022","journal-title":"JAMA Ophthalmol"},{"issue":"4","key":"bib34","doi-asserted-by":"publisher","first-page":"e191860","DOI":"10.1001\/jamanetworkopen.2019.1860","article-title":"Assessment of automated identification of phases in videos of cataract surgery using machine learning and deep learning techniques","volume":"2","author":"Yu","year":"2019","journal-title":"JAMA Netw Open"},{"key":"bib41","first-page":"2771","article-title":"Applied force during vitreoretinal microsurgery with handheld instruments","volume":"2004","author":"Jagtap","year":"2004","journal-title":"Conf Proc IEEE Eng Med Biol Soc"},{"issue":"1","key":"bib42","doi-asserted-by":"publisher","first-page":"200","DOI":"10.1097\/IAE.0b013e3182625d2b","article-title":"A force-sensing microsurgical instrument that detects forces below human tactile sensation","volume":"33","author":"Sunshine","year":"2013","journal-title":"Retina"},{"issue":"1","key":"bib43","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1136\/bjo.2006.096040","article-title":"Robotic ocular surgery","volume":"91","author":"Tsirbas","year":"2007","journal-title":"Br J Ophthalmol"},{"key":"bib44","doi-asserted-by":"publisher","first-page":"649","DOI":"10.1038\/s41551-018-0248-4","article-title":"First-in-human study of the safety and viability of intraocular robotic surgery","volume":"2","author":"Edwards","year":"2018","journal-title":"Nat Biomed Eng"},{"issue":"4","key":"bib45","doi-asserted-by":"publisher","first-page":"7750","DOI":"10.1109\/LRA.2021.3100937","article-title":"Spotlight-based 3D instrument guidance for autonomous task in robot-assisted retinal surgery","volume":"6","author":"Zhou","year":"2021","journal-title":"IEEE Robot Autom Lett"},{"key":"bib12","doi-asserted-by":"crossref","DOI":"10.1017\/9781108955652","volume-title":"Deep Learning in Science","author":"Baldi","year":"2021"},{"key":"bib35","doi-asserted-by":"crossref","DOI":"10.1109\/CVPR.2016.90","article-title":"Deep residual learning for image recognition","volume-title":"Presented at: Proceedings of the IEEE conference on computer vision and pattern recognition; June 27\u201320, 2016; Las Vegas, NV","author":"He"},{"key":"bib36","article-title":"ultralytics\/yolov5: v3.1 - Bug fixes and performance improvements. version v3.1. Zenodo","author":"Jocher","year":"2020"},{"key":"bib37","doi-asserted-by":"crossref","DOI":"10.1109\/CVPRW50498.2020.00203","article-title":"CSPNet: A new backbone that can enhance learning capability of CNN","volume-title":"Presented at: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition workshops; June 14\u201319, 2020; Virtual","author":"Wang"},{"key":"bib38","doi-asserted-by":"crossref","DOI":"10.1109\/CVPR.2018.00913","article-title":"Path aggregation network for instance segmentation","volume-title":"Presented at: Proceedings of the IEEE conference on computer vision and pattern recognition; June 18\u201322, 2018; Salt Lake City, Utah","author":"Liu"},{"key":"bib39","doi-asserted-by":"crossref","DOI":"10.1109\/CVPR.2017.106","article-title":"Feature pyramid networks for object detection","volume-title":"Presented at: Proceedings of the IEEE conference on computer vision and pattern recognition; July 21\u201326, 2017; Honolulu, Hawaii","author":"Lin"},{"key":"bib40","doi-asserted-by":"crossref","DOI":"10.1109\/CVPR.2009.5206848","article-title":"Imagenet: A large-scale hierarchical image database","volume-title":"Presented at: 2009 IEEE conference on computer vision and pattern recognition; June 20\u201325, 2009; Miami, Florida","author":"Deng"},{"key":"bib46","volume-title":"Surgical instrument tracking for intraoperative vitrectomy guidance using deep learning and stereo vision","author":"Fatta","year":"2020"}],"container-title":["Translational Vision Science & Technology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/tvst.arvojournals.org\/article.aspx?articleid=2785288","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,17]],"date-time":"2023-01-17T15:31:20Z","timestamp":1673969480000},"score":1,"resource":{"primary":{"URL":"https:\/\/tvst.arvojournals.org\/article.aspx?articleid=2785288"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1,17]]},"references-count":46,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2023,1,3]]}},"URL":"https:\/\/doi.org\/10.1167\/tvst.12.1.20","relation":{},"ISSN":["2164-2591"],"issn-type":[{"value":"2164-2591","type":"print"}],"subject":[],"published":{"date-parts":[[2023,1,17]]}}}