# Retinal Disease Classification

Retinal disease grading has mostly relied on raw color fundus photographs, where low-contrast lesions and thin vessels are easily lost to illumination and noise. F2D-RetinaNet sends an enhanced green channel and a vessel map through two separate branches and fuses them into one grading decision. On APTOS 2019 five-grade diabetic retinopathy staging it reaches 93.32% accuracy, 3.25 points above the RGB-only baseline, and 87.14% on the external DREAM-RFI set after overlapping images were excluded.

Retinal disease grading has mostly relied on raw color fundus photographs, where low-contrast lesions and thin vessels are easily lost to illumination and noise. F2D-RetinaNet sends an enhanced green channel and a vessel map through two separate branches and fuses them into one grading decision. On APTOS 2019 five-grade diabetic retinopathy staging it reaches 93.32% accuracy, 3.25 points above the RGB-only baseline, and 87.14% on the external DREAM-RFI set after overlapping images were excluded.