1 citations · 1 across the 3 of their papers we have counts for
4 papers
Benchmarking Ophthalmology Foundation Models for Clinically Significant Age Macular Degeneration Detection
Benjamin A. Cohen, Jonathan Fhima, Meishar Meisel +4
Self-supervised learning (SSL) has enabled Vision Transformers (ViTs) to learn robust representations from large-scale natural image datasets, enhancing their generalization across…
Enhancing Retinal Vessel Segmentation Generalization via Layout-Aware Generative Modelling
Jonathan Fhima, Jan Van Eijgen, Lennert Beeckmans +6
Generalization in medical segmentation models is challenging due to limited annotated datasets and imaging variability. To address this, we propose Retinal Layout-Aware Diffusion (…
GONet: A Generalizable Deep Learning Model for Glaucoma Detection
Or Abramovich, Hadas Pizem, Jonathan Fhima +8
Glaucomatous optic neuropathy (GON) is a prevalent ocular disease that can lead to irreversible vision loss if not detected early and treated. The traditional diagnostic approach f…
TAP-VL: Text Layout-Aware Pre-training for Enriched Vision-Language Models
Jonathan Fhima, Elad Ben Avraham, Oren Nuriel +4
Vision-Language (VL) models have garnered considerable research interest; however, they still face challenges in effectively handling text within images. To address this limitation…