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

COMMENTED

Retinal Diseases

Clinically applicable deep learning for diagnosis and referral in retinal disease

Nat Med.

De Fauw J, Ledsam JR, Romera-Paredes B, Nikolov S, Tomasev N, Blackwell S, Askham H, Glorot X, O'Donoghue B, Visentin D, van den Driessche G, Lakshminarayanan B, Meyer C, Mackinder F, Bouton S, Ayoub K, Chopra R, King D, Karthikesalingam A, Hughes CO, Raine R, Hughes J, Sim DA, Egan C, Tufail A, Montgomery H, Hassabis D, Rees G, Back T, Khaw PT, Suleyman M1, Cornebise J, Keane PA, Ronneberger O

doi: 10.1038/s41591-018-0107-6.

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

Macular DiseasesRetinal Diseases

Retinal single-layer analysis with optical coherence tomography shows inner retinal layer thinning in Huntington's disease as a potential biomarker

Int Ophthalmol.

Gulmez Sevim D, Unlu M, Gultekin M, Karaca C

doi: 10.1007/s10792-018-0857-7.

COMMENTED

Retinal Diseases

Identification of Retinal Biomarkers in Alzheimer's Disease Using Optical Coherence Tomography: Recent Insights, Challenges, and Opportunities

J Clin Med.

Cabrera DeBuc D, Gaca-Wysocka M, Grzybowski A, Kanclerz P

doi: 10.3390/jcm8070996.

Retinal Diseases

Segmentation error in spectral domain optical coherence tomography measures of the retinal nerve fibre layer thickness in idiopathic intracranial hypertension

BMC Ophthalmol.

Aojula A, Mollan SP, Horsburgh J, Yiangou A, Markey KA, Mitchell JL, Scotton WJ, Keane PA, Sinclair AJ

doi: 10.1186/s12886-017-0652-7.

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

Macular Diseases

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

JAMA Ophthalmol.

Mehta N, Lee CS, Mendonça LSM, Raza K, Braun PX, Duker JS, Waheed NK, Lee AY

doi: 10.1001/jamaophthalmol.

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

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