A Global and Patch-wise Contrastive Loss for Accurate Automated Exudate Detection

arXiv:2302.11517v2 Announce Type: replace-cross
Abstract: Diabetic retinopathy (DR) is a leading global cause of blindness. Early detection of hard exudates plays a crucial role in identifying DR, which aids in treating diabetes and preventing vision loss. However, the unique characteristics of hard exudates, ranging from their inconsistent shapes to indistinct boundaries, pose significant challenges to existing segmentation techniques. To address these issues, we present a novel supervised contrastive learning framework to optimize hard exudate segmentation. Specifically, we introduce a patch-wise …

abstract arxiv automated blindness cs.cv cs.lg detection diabetes eess.iv global loss role type vision wise