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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主要な著者:	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
フォーマット:	Artigo
言語:	Inglês
出版事項:	Elsevier 2025-03-01
シリーズ:	Ophthalmology Science
主題:	Age-related macular degeneration Artificial intelligence Deep learning Fundus autofluorescence imaging Geographic atrophy
オンライン･アクセス:	http://www.sciencedirect.com/science/article/pii/S2666914524001714
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