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6.8.2 Posterior segment (60)
Showing records 1 to 25
Display all abstracts in classification 6.8.2 Posterior segment
Search within classification 6.8.2 Posterior segment84993 Relationship between nerve fiber layer defect and the presence of epiretinal membrane in a Japanese population: The JPHC-NEXT Eye Study
Uchida A
Scientific reports 2020; 10: 779
84649 Localized Retinal Nerve Fiber Layer Defect Location Among Red-free Fundus Photographs, En Face Structural Images, and Cirrus HD-OCT Maps
Park JH
Journal of Glaucoma 2019; 28: 1054-1060
84550 Human Versus Machine: Comparing a Deep Learning Algorithm to Human Gradings for Detecting Glaucoma on Fundus Photographs
Jammal AA
American Journal of Ophthalmology 2020; 211: 123-131
85101 Diagnosis of Glaucoma on Retinal Fundus Images Using Deep Learning: Detection of Nerve Fiber Layer Defect and Optic Disc Analysis
Muramatsu C
Adv Exp Med Biol 2020; 1213: 121-132
84897 Characteristics of diffuse retinal nerve fiber layer defects in red-free photographs as observed in optical coherence tomography en face images
Lim AB
BMC Ophthalmology 2020; 20: 16
85073 Assessing the Impact of En Face Retinal Nerve Fiber Layer Imaging on Clinical Decision Making for Glaucoma Suspects
King BJ
Optometry and Vision Science 2020; 97: 54-61
84554 Relationship between ocular risk factors for glaucoma and optic disc rim in normal eyes
Iwase A
British Journal of Ophthalmology 2020; 104: 1120-1124
84734 Optic Disc and Cup Segmentation in Retinal Images for Glaucoma Diagnosis by Locally Statistical Active Contour Model with Structure Prior
Zhou W
Computational and mathematical methods in medicine 2019; 2019: 8973287
84506 Regional Patterns in Retinal Microvascular Network Geometry in Health and Disease
Popovic N
Scientific reports 2019; 9: 16340
85179 Offline computer-aided diagnosis for Glaucoma detection using fundus images targeted at mobile devices
Martins J
Computer Methods and Programs in Biomedicine 2020; 192: 105341
85039 Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs
Li F
Graefe's Archive for Clinical and Experimental Ophthalmology 2020; 258: 851-867
84734 Optic Disc and Cup Segmentation in Retinal Images for Glaucoma Diagnosis by Locally Statistical Active Contour Model with Structure Prior
Yi Y
Computational and mathematical methods in medicine 2019; 2019: 8973287
85039 Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs
Yan L
Graefe's Archive for Clinical and Experimental Ophthalmology 2020; 258: 851-867
85073 Assessing the Impact of En Face Retinal Nerve Fiber Layer Imaging on Clinical Decision Making for Glaucoma Suspects
Swanson WH
Optometry and Vision Science 2020; 97: 54-61
84506 Regional Patterns in Retinal Microvascular Network Geometry in Health and Disease
Vujosevic S
Scientific reports 2019; 9: 16340
84649 Localized Retinal Nerve Fiber Layer Defect Location Among Red-free Fundus Photographs, En Face Structural Images, and Cirrus HD-OCT Maps
Yoo C
Journal of Glaucoma 2019; 28: 1054-1060
84550 Human Versus Machine: Comparing a Deep Learning Algorithm to Human Gradings for Detecting Glaucoma on Fundus Photographs
Thompson AC
American Journal of Ophthalmology 2020; 211: 123-131
85179 Offline computer-aided diagnosis for Glaucoma detection using fundus images targeted at mobile devices
Cardoso JS
Computer Methods and Programs in Biomedicine 2020; 192: 105341
84897 Characteristics of diffuse retinal nerve fiber layer defects in red-free photographs as observed in optical coherence tomography en face images
Park JH
BMC Ophthalmology 2020; 20: 16
84993 Relationship between nerve fiber layer defect and the presence of epiretinal membrane in a Japanese population: The JPHC-NEXT Eye Study
Sasaki M
Scientific reports 2020; 10: 779
84554 Relationship between ocular risk factors for glaucoma and optic disc rim in normal eyes
Sawaguchi S
British Journal of Ophthalmology 2020; 104: 1120-1124
84993 Relationship between nerve fiber layer defect and the presence of epiretinal membrane in a Japanese population: The JPHC-NEXT Eye Study
Motomura K
Scientific reports 2020; 10: 779
84550 Human Versus Machine: Comparing a Deep Learning Algorithm to Human Gradings for Detecting Glaucoma on Fundus Photographs
Mariottoni EB
American Journal of Ophthalmology 2020; 211: 123-131
85073 Assessing the Impact of En Face Retinal Nerve Fiber Layer Imaging on Clinical Decision Making for Glaucoma Suspects
Klemencic SA
Optometry and Vision Science 2020; 97: 54-61
85039 Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs
Wang Y
Graefe's Archive for Clinical and Experimental Ophthalmology 2020; 258: 851-867
