Model-to-Data Approach for Deep Learning in Optical Coherence Tomography Intraretinal Fluid Segmentation

Retinal Diseases

Validation and Clinical Applicability of Whole-Volume Automated Segmentation of Optical Coherence Tomography in Retinal Disease Using Deep Learning

JAMA Ophthalmol

Wilson M, Chopra R, Wilson MZ, Cooper C, MacWilliams P, Liu Y, Wulczyn E, Florea D, Hughes CO, Karthikesalingam A, Khalid H, Vermeirsch S, Nicholson L, Keane PA, Balaskas K, Kelly CJ

doi: 10.1001/jamaophthalmol.2021.2273

Macular Diseases

Detection of oedema on optical coherence tomography images using deep learning model trained on noisy clinical data

Acta Ophthalmol

Potapenko I, Kristensen M, Thiesson B, Ilginis T, Lykke Sørensen T, Nouri Hajari J, Fuchs J, Hamann S, la Cour M

doi: 10.1111/aos.14895

COMMENTED

Glaucoma and Ocular Pressure

Assessment of a Segmentation-Free Deep Learning Algorithm for Diagnosing Glaucoma From Optical Coherence Tomography Scans

★ 1 Recommended by Prof. Dr emer. Josef Flammer, Faculty Member

★ 3 Recommended by Prof. Dr Ke Yao, Faculty Member

★ 3 Recommended and commented by Dr habil. Gábor Márk Somfai, PhD, Faculty Member

JAMA Ophthalmol.

Thompson AC, Jammal AA, Berchuck SI, Mariottoni EB, Medeiros FA

doi: 10.1001/jamaophthalmol.2019.5983.

Macular Diseases

Quantitative analysis of optical coherence tomography for neovascular age-related macular degeneration using deep learning

Ophthalmology

Moraes G, Fu DJ, Wilson M, Khalid H, Wagner SK, Korot E, Ferraz D, Faes L, Kelly CJ, Spitz T, Patel PJ, Balaskas K, Keenan TDL, Keane PA, Chopra R

doi: 10.1016/j.ophtha.2020.09.025

Retinal Diseases

Deep learning models for screening of high myopia using optical coherence tomography

Sci Rep

Choi KJ, Choi JE, Roh HC, Eun JS, Kim JM, Shin YK, Kang MC, Chung JK, Lee C, Lee D, Kang SW, Cho BH, Kim SJ

doi: 10.1038/s41598-021-00622-x

Retinal Diseases

Association of Optical Coherence Tomography Angiography of Collaterals in Retinal Vein Occlusion With Major Venous Outflow Through the Deep Vascular Complex

JAMA Ophthalmol.

Freund KB, Sarraf D, Leong BCS, Garrity ST, Vupparaboina KK, Dansingani KK

doi: 10.1001/jamaophthalmol.

Uveitis

Optical coherence tomography and optical coherence tomography angiography in uveitis: a review

Clin Exp Ophthalmol.

Invernizzi A, Cozzi M, Staurenghi G

doi: 10.1111/ceo.13470.

Macular Diseases

Feasibility of support vector machine learning in age-related macular degeneration using small sample yielding sparse optical coherence tomography data

Acta Ophthalmol.

Quellec G, Kowal J, Hasler PW, Scholl HPN, Zweifel S, Konstantinos B, de Carvalho JER, Heeren T, Egan C, Tufail A, Maloca PM

doi: 10.1111/aos.14055.

Macular Diseases

Deep Learning Estimation of 10-2 and 24-2 Visual Field Metrics based on Thickness Maps from Macula Optical Coherence Tomography

Ophthalmology

Christopher M, Bowd C, Proudfoot JA, Belghith A, Goldbaum MH, Rezapour J, Fazio MA, Girkin CA, De Moraes G, Liebmann JM, Weinreb RN, Zangwill LM

doi: 10.1016/j.ophtha.2021.04.022

Related content

Validation and Clinical Applicability of Whole-Volume Automated Segmentation of Optical Coherence Tomography in Retinal Disease Using Deep Learning

Detection of oedema on optical coherence tomography images using deep learning model trained on noisy clinical data

Assessment of a Segmentation-Free Deep Learning Algorithm for Diagnosing Glaucoma From Optical Coherence Tomography Scans

Quantitative analysis of optical coherence tomography for neovascular age-related macular degeneration using deep learning

Deep learning models for screening of high myopia using optical coherence tomography

Association of Optical Coherence Tomography Angiography of Collaterals in Retinal Vein Occlusion With Major Venous Outflow Through the Deep Vascular Complex

Optical coherence tomography and optical coherence tomography angiography in uveitis: a review

Feasibility of support vector machine learning in age-related macular degeneration using small sample yielding sparse optical coherence tomography data

Deep Learning Estimation of 10-2 and 24-2 Visual Field Metrics based on Thickness Maps from Macula Optical Coherence Tomography