{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,19]],"date-time":"2026-05-19T23:04:39Z","timestamp":1779231879987,"version":"3.51.4"},"reference-count":42,"publisher":"Association for Research in Vision and Ophthalmology (ARVO)","issue":"10","license":[{"start":{"date-parts":[[2023,10,13]],"date-time":"2023-10-13T00:00:00Z","timestamp":1697155200000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Trans. Vis. Sci. Tech."],"published-print":{"date-parts":[[2023,10,13]]},"DOI":"10.1167\/tvst.12.10.10","type":"journal-article","created":{"date-parts":[[2023,10,13]],"date-time":"2023-10-13T15:30:57Z","timestamp":1697211057000},"page":"10","source":"Crossref","is-referenced-by-count":4,"title":["Improving the Accuracy and Speed of Visual Field Testing in Glaucoma With Structural Information and Deep Learning"],"prefix":"10.1167","volume":"12","author":[{"given":"Giovanni","family":"Montesano","sequence":"first","affiliation":[{"name":"City, University of London, Optometry and Visual Sciences, London, UK"},{"name":"NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Georgios","family":"Lazaridis","sequence":"additional","affiliation":[{"name":"City, University of London, Optometry and Visual Sciences, London, UK"},{"name":"NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK"},{"name":"Centre for Medical Image Computing, University College London, London, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Giovanni","family":"Ometto","sequence":"additional","affiliation":[{"name":"City, University of London, Optometry and Visual Sciences, London, UK"},{"name":"NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David P.","family":"Crabb","sequence":"additional","affiliation":[{"name":"City, University of London, Optometry and Visual Sciences, London, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David F.","family":"Garway-Heath","sequence":"additional","affiliation":[{"name":"NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"27","reference":[{"key":"bib1","first-page":"2654","article-title":"Properties of perimetric threshold estimates from full threshold, SITA Standard, and SITA Fast strategies","volume":"43","author":"Artes","year":"2002","journal-title":"Invest Ophthalmol Vis Sci"},{"key":"bib2","doi-asserted-by":"publisher","first-page":"e003996","DOI":"10.1136\/bmjopen-2013-003996","article-title":"A qualitative investigation into patients\u2019 views on visual field testing for glaucoma monitoring","volume":"4","author":"Glen","year":"2014","journal-title":"BMJ Open"},{"key":"bib3","first-page":"417","article-title":"Response variability in the visual field: comparison of optic neuritis, glaucoma, ocular hypertension, and normal eyes","volume":"41","author":"Henson","year":"2000","journal-title":"Invest Ophthalmol Vis Sci"},{"key":"bib4","doi-asserted-by":"publisher","first-page":"688","DOI":"10.1016\/j.preteyeres.2007.08.001","article-title":"A framework for comparing structural and functional measures of glaucomatous damage","volume":"26","author":"Hood","year":"2007","journal-title":"Prog Retin Eye Res"},{"key":"bib5","doi-asserted-by":"publisher","first-page":"6320","DOI":"10.1167\/iovs.15-17450","article-title":"Influence of the retinal blood vessel topography on the variability of the retinal nerve fiber bundle trajectories in the human retina","volume":"56","author":"Qiu","year":"2015","journal-title":"Invest Ophthalmol Vis Sci"},{"key":"bib6","doi-asserted-by":"publisher","first-page":"1695","DOI":"10.1016\/j.ophtha.2015.04.021","article-title":"Enhancing structure\u2013function correlations in glaucoma with customized spatial mapping","volume":"122","author":"Ballae Ganeshrao","year":"2015","journal-title":"Ophthalmology"},{"key":"bib7","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1167\/tvst.10.1.19","article-title":"Improving personalized structure to function mapping from optic nerve head to visual field","volume":"10","author":"Turpin","year":"2021","journal-title":"Transl Vis Sci Technol"},{"key":"bib8","doi-asserted-by":"publisher","first-page":"6074","DOI":"10.1167\/iovs.13-11902","article-title":"The influence of intersubject variability in ocular anatomical variables on the mapping of retinal locations to the retinal nerve fiber layer and optic nerve head","volume":"54","author":"Lamparter","year":"2013","journal-title":"Invest Ophthalmol Vis Sci"},{"key":"bib9","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1016\/j.ajo.2021.12.020","article-title":"Predicting visual fields from optical coherence tomography via an ensemble of deep representation learners","volume":"238","author":"Lazaridis","year":"2022","journal-title":"Am J Ophthalmol"},{"key":"bib10","doi-asserted-by":"publisher","first-page":"781","DOI":"10.1016\/j.ophtha.2022.02.017","article-title":"Policy-driven, multimodal deep learning for predicting visual fields from the optic disc and OCT imaging","volume":"129","author":"Kihara","year":"2022","journal-title":"Ophthalmology"},{"key":"bib11","doi-asserted-by":"publisher","first-page":"12562","DOI":"10.1038\/s41598-021-91493-9","article-title":"RetiNerveNet: using recursive deep learning to estimate pointwise 24-2 visual field data based on retinal structure","volume":"11","author":"Datta","year":"2021","journal-title":"Sci Rep"},{"key":"bib12","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1167\/tvst.9.2.19","article-title":"Artificial intelligence mapping of structure to function in glaucoma","volume":"9","author":"Mariottoni","year":"2020","journal-title":"Transl Vis Sci Technol"},{"key":"bib13","doi-asserted-by":"publisher","first-page":"e0234902","DOI":"10.1371\/journal.pone.0234902","article-title":"A deep learning approach to predict visual field using optical coherence tomography","volume":"15","author":"Park","year":"2020","journal-title":"PLoS One"},{"key":"bib14","doi-asserted-by":"publisher","first-page":"507","DOI":"10.1136\/bjophthalmol-2019-315600","article-title":"Deep learning model to predict visual field in central 10 degrees from optical coherence tomography measurement in glaucoma","volume":"105","author":"Hashimoto","year":"2021","journal-title":"Br J Ophthalmol"},{"key":"bib15","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1097\/OPX.0000000000000447","article-title":"A perimetric test procedure that uses structural information","volume":"92","author":"Ganeshrao","year":"2015","journal-title":"Optom Vis Sci"},{"key":"bib16","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1167\/tvst.7.6.36","article-title":"Improving visual field examination of the macula using structural information","volume":"7","author":"Montesano","year":"2018","journal-title":"Transl Vis Sci Technol"},{"key":"bib17","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1167\/tvst.2.4.3","article-title":"Towards patient-tailored perimetry: automated perimetry can be improved by seeding procedures with patient-specific structural information","volume":"2","author":"Denniss","year":"2013","journal-title":"Transl Vis Sci Technol"},{"key":"bib18","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1167\/12.11.22","article-title":"The Open Perimetry Interface: an enabling tool for clinical visual psychophysics","volume":"12","author":"Turpin","year":"2012","journal-title":"J Vis"},{"key":"bib19","first-page":"T4","article-title":"Evaluation of visual field and imaging outcomes for glaucoma clinical trials (an American Ophthalomological Society thesis)","volume":"115","author":"Garway-Heath","year":"2017","journal-title":"Trans Am Ophthalmol Soc"},{"key":"bib20","doi-asserted-by":"publisher","first-page":"242","DOI":"10.1016\/j.ophtha.2018.08.010","article-title":"A comparison between the compass fundus perimeter and the Humphrey Field Analyzer","volume":"126","author":"Montesano","year":"2019","journal-title":"Ophthalmology"},{"key":"bib22","doi-asserted-by":"publisher","first-page":"885","DOI":"10.1016\/0042-6989(94)90039-6","article-title":"Efficient and unbiased modifications of the QUEST threshold method: theory, simulations, experimental evaluation and practical implementation","volume":"34","author":"King-Smith","year":"1994","journal-title":"Vision Res"},{"key":"bib23","doi-asserted-by":"publisher","first-page":"981","DOI":"10.1097\/01.opx.0000187841.08676.36","article-title":"Advantages of terminating zippy estimation by sequential testing (ZEST) with dynamic criteria for white-on-white perimetry","volume":"82","author":"McKendrick","year":"2005","journal-title":"Optom Vis Sci"},{"key":"bib24","doi-asserted-by":"publisher","first-page":"4787","DOI":"10.1167\/iovs.03-0023","article-title":"Properties of perimetric threshold estimates from full threshold, ZEST, and SITA-like strategies, as determined by computer simulation","volume":"44","author":"Turpin","year":"2003","journal-title":"Invest Ophthalmol Vis Sci"},{"key":"bib25","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1167\/tvst.5.2.7","article-title":"Incorporating spatial models in visual field test procedures","volume":"5","author":"Rubinstein","year":"2016","journal-title":"Transl Vis Sci Technol"},{"key":"bib26","doi-asserted-by":"publisher","first-page":"4283","DOI":"10.1167\/iovs.15-16691","article-title":"Global visit effects in point-wise longitudinal modeling of glaucomatous visual fields","volume":"56","author":"Bryan","year":"2015","journal-title":"Invest Ophthalmol Vis Sci"},{"key":"bib27","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1167\/tvst.7.3.22","article-title":"Development of a visual field simulation model of longitudinal point-wise sensitivity changes from a clinical glaucoma cohort","volume":"7","author":"Wu","year":"2018","journal-title":"Transl Vis Sci Technol"},{"key":"bib28","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1016\/j.ajo.2021.04.008","article-title":"Improving the power of glaucoma neuroprotection trials using existing visual field data","volume":"229","author":"Montesano","year":"2021","journal-title":"Am J Ophthalmol"},{"key":"bib29","doi-asserted-by":"publisher","first-page":"1","DOI":"10.18637\/jss.v067.i01","article-title":"Fitting linear mixed-effects models using lme4","volume":"67","author":"Bates","year":"2015","journal-title":"J Stat Softw"},{"key":"bib30","doi-asserted-by":"publisher","first-page":"3237","DOI":"10.1167\/iovs.10-6255","article-title":"What reduction in standard automated perimetry variability would improve the detection of visual field progression?","volume":"52","author":"Turpin","year":"2011","journal-title":"Invest Ophthalmol Vis Sci"},{"key":"bib31","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1016\/j.ajo.2021.04.008","article-title":"Improving the power of glaucoma neuroprotection trials using existing visual field data","volume":"229","author":"Montesano","year":"2021","journal-title":"Am J Ophthalmol"},{"key":"bib32","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1167\/tvst.10.12.4","article-title":"Hierarchical censored Bayesian analysis of visual field progression","volume":"10","author":"Montesano","year":"2021","journal-title":"Transl Vis Sci Technol"},{"key":"bib33","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1167\/tvst.11.8.3","article-title":"Long- and short-term variability of perimetry in glaucoma","volume":"11","author":"Gardiner","year":"2022","journal-title":"Transl Vis Sci Technol"},{"key":"bib34","doi-asserted-by":"publisher","first-page":"554","DOI":"10.1016\/j.ophtha.2016.12.016","article-title":"The proportion of individuals likely to benefit from customized optic nerve head structure\u2013function mapping","volume":"124","author":"McKendrick","year":"2017","journal-title":"Ophthalmology"},{"key":"bib35","doi-asserted-by":"publisher","first-page":"e188029","DOI":"10.1001\/jamanetworkopen.2018.8029","article-title":"Estimating retinal sensitivity using optical coherence tomography with deep-learning algorithms in macular telangiectasia type 2","volume":"2","author":"Kihara","year":"2019","journal-title":"JAMA Netw Open"},{"key":"bib36","doi-asserted-by":"crossref","first-page":"501","DOI":"10.1016\/j.oret.2022.01.021","article-title":"Linking function and structure with ReSensNet: predicting retinal sensitivity from OCT using deep learning","volume":"5","author":"Seebock","year":"2022","journal-title":"Ophthalmol Retina"},{"key":"bib37","doi-asserted-by":"publisher","first-page":"1167","DOI":"10.1001\/archophthalmol.2011.112","article-title":"Quantifying discordance between structure and function measurements in the clinical assessment of glaucoma","volume":"129","author":"Zhu","year":"2011","journal-title":"Arch Ophthalmol"},{"key":"bib38","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1167\/tvst.5.2.15","article-title":"The 24-2 visual field test misses central macular damage confirmed by the 10-2 Visual field test and optical coherence tomography","volume":"5","author":"Grillo","year":"2016","journal-title":"Transl Vis Sci Technol"},{"key":"bib39","doi-asserted-by":"publisher","first-page":"1449","DOI":"10.1016\/j.ophtha.2017.04.021","article-title":"24-2 visual fields miss central defects shown on 10-2 tests in glaucoma suspects, ocular hypertensives, and early glaucoma","volume":"124","author":"De Moraes","year":"2017","journal-title":"Ophthalmology"},{"key":"bib40","doi-asserted-by":"publisher","first-page":"1722","DOI":"10.1016\/j.ophtha.2021.06.012","article-title":"Do additional testing locations improve the detection of macular perimetric defects in glaucoma?","volume":"128","author":"Montesano","year":"2021","journal-title":"Ophthalmology"},{"key":"bib41","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1167\/tvst.9.13.24","article-title":"Increasing the spatial resolution of visual field tests without increasing test duration: an evaluation of ARREST","volume":"9","author":"Muthusamy","year":"2020","journal-title":"Transl Vis Sci Technol"},{"key":"bib42","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1167\/tvst.5.5.1","article-title":"Assessing the GOANNA visual field algorithm using artificial scotoma generation on human observers","volume":"5","author":"Chong","year":"2016","journal-title":"Transl Vis Sci Technol"},{"key":"bib21","doi-asserted-by":"crossref","first-page":"785","DOI":"10.1145\/2939672.2939785","article-title":"Xgboost: a scalable tree boosting system","volume-title":"Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","author":"Chen","year":"2016"}],"container-title":["Translational Vision Science &amp; Technology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/tvst.arvojournals.org\/article.aspx?articleid=2792922","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,13]],"date-time":"2023-10-13T15:31:01Z","timestamp":1697211061000},"score":1,"resource":{"primary":{"URL":"https:\/\/tvst.arvojournals.org\/article.aspx?articleid=2792922"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,13]]},"references-count":42,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2023,10,3]]}},"URL":"https:\/\/doi.org\/10.1167\/tvst.12.10.10","relation":{},"ISSN":["2164-2591"],"issn-type":[{"value":"2164-2591","type":"print"}],"subject":[],"published":{"date-parts":[[2023,10,13]]}}}