Deep Learning Models for Justified Referral in AI Glaucoma Screening

Glaucoma is an optic disease that leads to blindness, but this might be avoided with an early diagnosis thanks to a screening test. The JustRAIGS Challenge was organised to develop solutions for glaucoma screening from retinal fundus images that not only classify fundus images as "referrable" or "no referable" but also identify specific characteristics or abnormalities that may be present in the fundus images of glaucoma patients. In this work, we present our solution to this challenge based on the study of several combinations of fundus images and their associated optic disc and cup. For the binary task, our solution consists of the ensemble of a ConvNext model and a Swin model that achieves a sensitivity at 95% specificity of 0.8570; whereas, for the multi-label task, our ConvNext model achieved a Hamming Loss of 0.1930.