RetinaRegen: A Hybrid Model for Readability and Detail Restoration in Fundus Images
Journal:
arXiv
Published Date:
Feb 26, 2025
Abstract
Fundus image quality is crucial for diagnosing eye diseases, but real-world
conditions often result in blurred or unreadable images, increasing diagnostic
uncertainty. To address these challenges, this study proposes RetinaRegen, a
hybrid model for retinal image restoration that integrates a readability
classifi-cation model, a Diffusion Model, and a Variational Autoencoder (VAE).
Ex-periments on the SynFundus-1M dataset show that the proposed method achieves
a PSNR of 27.4521, an SSIM of 0.9556, and an LPIPS of 0.1911 for the
readability labels of the optic disc (RO) region. These results demonstrate
superior performance in restoring key regions, offering an effective solution
to enhance fundus image quality and support clinical diagnosis.
