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Physics-informed deep generative learning for quantitative assessment of the retina

Medicine and Health

Physics-informed deep generative learning for quantitative assessment of the retina

E. E. Brown, A. A. Guy, et al.

Discover a groundbreaking algorithmic approach that revolutionizes the generation of realistic digital models of human retinal blood vessels. This innovative method, developed by Emmeline E. Brown and colleagues, surpasses traditional labeling performance through physics-informed generative adversarial networks, paving the way for enhanced early detection and monitoring of retinal diseases.

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