Detecting multiple retinal diseases in ultra-widefield fundus imaging and data-driven identification of informative regions with deep learning

作者：Justin Engelmann, Alice McTrusty, Ian J. C. MacCormick, Emma Pead, Amos Storkey, Miguel Oscar Bernabeu · 发表于：Nature Machine Intelligence · 年份：2022 · DOI：10.1038/s42256-022-00566-5 · 被引用次数：35 · 研究领域：Retinal Imaging and Analysis、Retinal and Optic Conditions、Ocular Diseases and Behçet’s Syndrome

Advances in ultra-widefield retinal imaging have created a need for automated disease detection. Engelmann and colleagues develop a deep learning model for the detection of retinal diseases. They evaluate it under more realistic conditions than has been considered previously and investigate what regions of ultra-widefield images are important for the performance of such a model.