Geographic Atrophy

Bayesian techniques outperform traditional models in geographic atrophy segmentation

Bayesian deep learning techniques, such as Monte Carlo dropout and ensemble methods, not only improve the accuracy of geographic atrophy (GA) segmentation compared to traditional models but also provide valuable pixel-wise estimates of uncertainty, according to a study. The retrospective analysis included 126 eyes from 87 participants in the SWAGGER...