Diffusion Autoencoder for Unsupervised Artifact Restoration in Handheld Fundus Images

ArXi:2604.15723v1 Announce Type: cross The advent of handheld fundus imaging devices has made ophthalmologic diagnosis and disease screening accessible, efficient, and cost-effective. However, images captured from these setups often suffer from artifacts such as flash reflections, exposure variations, and motion-induced blur, which degrade image quality and hinder downstream analysis.