Deep Learning to Predict the Future Growth of Geographic Atrophy from Fundus Autofluorescence

Deep Learning to Predict the Future Growth of Geographic Atrophy from Fundus Autofluorescence

Purpose: The region of growth (ROG) of geographic atrophy (GA) throughout the macular area has an impact on visual outcomes. Here, we developed multiple deep learning models to predict the 1-year ROG of GA lesions using fundus autofluorescence (FAF) images. Design: In this retrospective analysis, 3...

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Bibliographic Details
Main Authors: Anish Salvi, MS, Julia Cluceru, PhD, Simon S. Gao, PhD, Christina Rabe, PhD, Courtney Schiffman, PhD, Qi Yang, PhD, Aaron Y. Lee, MD, MSCI, Pearse A. Keane, MD, FRCOphth, Srinivas R. Sadda, MD, Frank G. Holz, MD, Daniela Ferrara, MD, PhD, Neha Anegondi, MTech
Format: Article
Language:English
Published: Elsevier 2025-03-01
Series:Ophthalmology Science
Subjects:
Age-related macular degeneration
Artificial intelligence
Deep learning
Fundus autofluorescence imaging
Geographic atrophy
Online Access:http://www.sciencedirect.com/science/article/pii/S2666914524001714
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