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182 related items for PubMed ID: 31914958
1. Characteristics of diffuse retinal nerve fiber layer defects in red-free photographs as observed in optical coherence tomography en face images. Lim AB, Park JH, Jung JH, Yoo C, Kim YY. BMC Ophthalmol; 2020 Jan 08; 20(1):16. PubMed ID: 31914958 [Abstract] [Full Text] [Related]
3. Comparison of the Progression of Localized Retinal Nerve Fiber Layer Defects in Red-free Fundus Photograph, En Face Structural Image, and OCT Angiography Image. Ji MJ, Park JH, Yoo C, Kim YY. J Glaucoma; 2020 Aug 08; 29(8):698-703. PubMed ID: 32398586 [Abstract] [Full Text] [Related]
4. Localized Retinal Nerve Fiber Layer Defects in Red-free Photographs Versus En Face Structural Optical Coherence Tomography Images. Jung JH, Park JH, Yoo C, Kim YY. J Glaucoma; 2018 Mar 08; 27(3):269-274. PubMed ID: 29303874 [Abstract] [Full Text] [Related]
5. Ability of cirrus high-definition spectral-domain optical coherence tomography clock-hour, deviation, and thickness maps in detecting photographic retinal nerve fiber layer abnormalities. Hwang YH, Kim YY, Kim HK, Sohn YH. Ophthalmology; 2013 Jul 08; 120(7):1380-7. PubMed ID: 23541761 [Abstract] [Full Text] [Related]
6. Agreement of retinal nerve fiber layer defect location between red-free fundus photography and cirrus HD-OCT maps. Hwang YH, Kim YY, Kim HK, Sohn YH. Curr Eye Res; 2014 Nov 08; 39(11):1099-105. PubMed ID: 24749850 [Abstract] [Full Text] [Related]
12. Three-dimensional imaging of the macular retinal nerve fiber layer in glaucoma with spectral-domain optical coherence tomography. Sakamoto A, Hangai M, Nukada M, Nakanishi H, Mori S, Kotera Y, Inoue R, Yoshimura N. Invest Ophthalmol Vis Sci; 2010 Oct 08; 51(10):5062-70. PubMed ID: 20463326 [Abstract] [Full Text] [Related]
14. Correlation between topographic profiles of localized retinal nerve fiber layer defects as determined by optical coherence tomography and red-free fundus photography. Hwang JM, Kim TW, Park KH, Kim DM, Kim H. J Glaucoma; 2006 Jun 08; 15(3):223-8. PubMed ID: 16778645 [Abstract] [Full Text] [Related]
15. From Machine to Machine: An OCT-Trained Deep Learning Algorithm for Objective Quantification of Glaucomatous Damage in Fundus Photographs. Medeiros FA, Jammal AA, Thompson AC. Ophthalmology; 2019 Apr 08; 126(4):513-521. PubMed ID: 30578810 [Abstract] [Full Text] [Related]
16. Diffuse glaucomatous structural and functional damage in the hemifield without significant pattern loss. Grewal DS, Sehi M, Greenfield DS. Arch Ophthalmol; 2009 Nov 08; 127(11):1442-8. PubMed ID: 19901209 [Abstract] [Full Text] [Related]
17. Comparison of sensitivities for detecting diffuse and localized retinal nerve fiber layer defects with time-domain optical coherence tomography in patients with glaucoma. Yoo YC, Park KH. J Glaucoma; 2013 Sep 08; 22(7):559-64. PubMed ID: 22274673 [Abstract] [Full Text] [Related]
18. Parapapillary deep-layer microvasculature dropout is only found near the retinal nerve fibre layer defect location in open-angle glaucoma. Son KY, Han JC, Kee C. Acta Ophthalmol; 2022 Feb 08; 100(1):e174-e180. PubMed ID: 33742532 [Abstract] [Full Text] [Related]
19. Trend-based analysis of retinal nerve fiber layer thickness measured by optical coherence tomography in eyes with localized nerve fiber layer defects. Lee EJ, Kim TW, Weinreb RN, Park KH, Kim SH, Kim DM. Invest Ophthalmol Vis Sci; 2011 Feb 28; 52(2):1138-44. PubMed ID: 21051691 [Abstract] [Full Text] [Related]
20. Detection of Progressive Glaucomatous Optic Nerve Damage on Fundus Photographs with Deep Learning. Medeiros FA, Jammal AA, Mariottoni EB. Ophthalmology; 2021 Mar 28; 128(3):383-392. PubMed ID: 32735906 [Abstract] [Full Text] [Related] Page: [Next] [New Search]