Topic
ophthalmology
New AI Framework Synthesizes Fluorescein Angiography from Fundus and Sparse OCT Scans
A research team led by Ma introduced a novel deep learning framework that synthesizes fluorescein angiography (FFA) from color fundus photography (CFP) using structural guidance from sparse optical coherence tomography (OCT) scans. The method uses a tri-modally aligned dataset of 3,676 patient eyes and achieves superior synthesis and downstream diagnosis performance compared to existing methods.
EyeMVP AI Model Enhances Retinal Screening by Learning OCT Insights from Fundus Photos
Researchers developed EyeMVP, a cross-modal retinal foundation model that enriches color fundus photography (CFP) with depth-resolved information from optical coherence tomography (OCT). Pretrained on 674,893 paired images from 112,642 patients across eight Chinese hospitals, EyeMVP outperforms leading models on 16 downstream tasks including macular edema detection (AUROC 0.948 vs 0.852) and myopic macular schisis (0.825).