These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
312 related articles for article (PubMed ID: 31824393)
1. Normative Data and Minimally Detectable Change for Inner Retinal Layer Thicknesses Using a Semi-automated OCT Image Segmentation Pipeline. Motamedi S; Gawlik K; Ayadi N; Zimmermann HG; Asseyer S; Bereuter C; Mikolajczak J; Paul F; Kadas EM; Brandt AU Front Neurol; 2019; 10():1117. PubMed ID: 31824393 [TBL] [Abstract][Full Text] [Related]
2. Normative Data and Conversion Equation for Spectral-Domain Optical Coherence Tomography in an International Healthy Control Cohort. Kenney R; Liu M; Hasanaj L; Joseph B; Al-Hassan AA; Balk L; Behbehani R; Brandt AU; Calabresi PA; Frohman EM; Frohman T; Havla J; Hemmer B; Jiang H; Knier B; Korn T; Leocani L; Martínez-Lapiscina EH; Papadopoulou A; Paul F; Petzold A; Pisa M; Villoslada P; Zimmermann H; Ishikawa H; Schuman JS; Wollstein G; Chen Y; Saidha S; Thorpe LE; Galetta SL; Balcer LJ; J Neuroophthalmol; 2022 Dec; 42(4):442-453. PubMed ID: 36049213 [TBL] [Abstract][Full Text] [Related]
3. Diagnostic Accuracy of Spectralis SD OCT Automated Macular Layers Segmentation to Discriminate Normal from Early Glaucomatous Eyes. Pazos M; Dyrda AA; Biarnés M; Gómez A; Martín C; Mora C; Fatti G; Antón A Ophthalmology; 2017 Aug; 124(8):1218-1228. PubMed ID: 28461015 [TBL] [Abstract][Full Text] [Related]
4. Effect of optic disc-fovea distance on the normative classifications of macular inner retinal layers as assessed with OCT in healthy subjects. Qiu K; Chen B; Yang J; Zheng C; Chen H; Zhang M; Jansonius NM Br J Ophthalmol; 2019 Jun; 103(6):821-825. PubMed ID: 30100556 [TBL] [Abstract][Full Text] [Related]
5. Comparison of point estimates and average thicknesses of retinal layers measured using manual optical coherence tomography segmentation for quantification of retinal neurodegeneration in multiple sclerosis. Sotirchos ES; Seigo MA; Calabresi PA; Saidha S Curr Eye Res; 2013 Jan; 38(1):224-8. PubMed ID: 22954302 [TBL] [Abstract][Full Text] [Related]
6. Retinal layer segmentation in patients with multiple sclerosis using spectral domain optical coherence tomography. Garcia-Martin E; Polo V; Larrosa JM; Marques ML; Herrero R; Martin J; Ara JR; Fernandez J; Pablo LE Ophthalmology; 2014 Feb; 121(2):573-9. PubMed ID: 24268855 [TBL] [Abstract][Full Text] [Related]
7. Retinal layer segmentation in a cohort of healthy children via optical coherence tomography. Runge AK; Remlinger J; Abegg M; Ferrazzini T; Brügger D; Weigt-Usinger K; Lücke T; Gold R; Salmen A PLoS One; 2022; 17(11):e0276958. PubMed ID: 36327296 [TBL] [Abstract][Full Text] [Related]
8. Normative Data for Retinal-Layer Thickness Maps Generated by Spectral-Domain OCT in a White Population. Invernizzi A; Pellegrini M; Acquistapace A; Benatti E; Erba S; Cozzi M; Cigada M; Viola F; Gillies M; Staurenghi G Ophthalmol Retina; 2018 Aug; 2(8):808-815.e1. PubMed ID: 31047534 [TBL] [Abstract][Full Text] [Related]
9. Comparison of the Abilities of SD-OCT and SS-OCT in Evaluating the Thickness of the Macular Inner Retinal Layer for Glaucoma Diagnosis. Lee KM; Lee EJ; Kim TW; Kim H PLoS One; 2016; 11(1):e0147964. PubMed ID: 26812064 [TBL] [Abstract][Full Text] [Related]
10. Normative Database for All Retinal Layer Thicknesses Using SD-OCT Posterior Pole Algorithm and the Effects of Age, Gender and Axial Lenght. Palazon-Cabanes A; Palazon-Cabanes B; Rubio-Velazquez E; Lopez-Bernal MD; Garcia-Medina JJ; Villegas-Perez MP J Clin Med; 2020 Oct; 9(10):. PubMed ID: 33076558 [TBL] [Abstract][Full Text] [Related]
11. Analysis of Agreement of Retinal-Layer Thickness Measures Derived from the Segmentation of Horizontal and Vertical Spectralis OCT Macular Scans. Gonzalez Caldito N; Antony B; He Y; Lang A; Nguyen J; Rothman A; Ogbuokiri E; Avornu A; Balcer L; Frohman E; Frohman TC; Bhargava P; Prince J; Calabresi PA; Saidha S Curr Eye Res; 2018 Mar; 43(3):415-423. PubMed ID: 29240464 [TBL] [Abstract][Full Text] [Related]
12. In vivo assessment of retinal neuronal layers in multiple sclerosis with manual and automated optical coherence tomography segmentation techniques. Seigo MA; Sotirchos ES; Newsome S; Babiarz A; Eckstein C; Ford E; Oakley JD; Syc SB; Frohman TC; Ratchford JN; Balcer LJ; Frohman EM; Calabresi PA; Saidha S J Neurol; 2012 Oct; 259(10):2119-30. PubMed ID: 22418995 [TBL] [Abstract][Full Text] [Related]
13. Segmented inner plexiform layer thickness as a potential biomarker to evaluate open-angle glaucoma: Dendritic degeneration of retinal ganglion cell. Kim EK; Park HL; Park CK PLoS One; 2017; 12(8):e0182404. PubMed ID: 28771565 [TBL] [Abstract][Full Text] [Related]
14. Thickness of individual layers at the macula and associated factors: the Beijing Eye Study 2011. Wang Q; Wei WB; Wang YX; Yan YN; Yang JY; Zhou WJ; Chan SY; Xu L; Jonas JB BMC Ophthalmol; 2020 Feb; 20(1):49. PubMed ID: 32050936 [TBL] [Abstract][Full Text] [Related]
15. Retinal layer thicknesses and neurodegeneration in early age-related macular degeneration: insights from the Coimbra Eye Study. Farinha C; Silva AL; Coimbra R; Nunes S; Cachulo ML; Marques JP; Pires I; Cunha-Vaz J; Silva R Graefes Arch Clin Exp Ophthalmol; 2021 Sep; 259(9):2545-2557. PubMed ID: 33738626 [TBL] [Abstract][Full Text] [Related]