AI RESEARCH
Cross-Modal Semantic-Enhanced Diffusion Framework for Diabetic Retinopathy Grading
arXiv CS.CV
•
ArXi:2605.09242v1 Announce Type: cross Automated grading of diabetic retinopathy (DR) faces several critical challenges: subtle inter-grade visual distinctions in fine-grained lesion patterns, distributional discrepancies induced by heterogeneous imaging devices and acquisition conditions, and the inherent inability of purely visual approaches to exploit clinical semantic knowledge. In this paper, we propose CLIP-Guided Semantic Diffusion (CGSD), a DR grading framework that synergistically integrates vision-language pre.