Natsuda Kaothanthong, Jirawut Limwattanayingyong, Sukhum Silpa-Archa, Mongkol Tadarati, Atchara Amphornphruet, Panisa Singhanetr, Pawas Lalitwongsa, Pantid Chantangphol, Anyarak Amornpetchsathaporn, Methaphon Chainakul, Paisan Ruamviboonsuk
We compared the performance of deep learning (DL) in the classification of optical coherence tomography (OCT) images of macular diseases between automated classification alone and in combination with automated segmentation. OCT images were collected from patients with neovascular age-related macular degeneration, polypoidal choroidal vasculopathy, diabetic macular edema, retinal vein occlusion, cystoid macular edema in Irvine-Gass syndrome, and other macular diseases, along with the normal fellow eyes. A total of 14,327 OCT images were used to train DL models...
January 4, 2023: Diagnostics