Federico Ricardi, Jonathan Oakley, Daniel Russakoff, Giacomo Boscia, Paolo Caselgrandi, Francesco Gelormini, Andrea Ghilardi, Giulia Pintore, Tommaso Tibaldi, Paola Marolo, Francesco Bandello, Michele Reibaldi, Enrico Borrelli
PURPOSE: To develop and validate a deep learning model for the segmentation of five retinal biomarkers associated with neovascular age-related macular degeneration (nAMD). METHODS: 300 optical coherence tomography volumes from subject eyes with nAMD were collected. Images were manually segmented for the presence of five crucial nAMD features: intraretinal fluid, subretinal fluid, subretinal hyperreflective material, drusen/drusenoid pigment epithelium detachment (PED) and neovascular PED...
March 14, 2024: British Journal of Ophthalmology