Explainable Severity Ranking via Pairwise n-Hidden Comparison: Case Study of Glaucoma

Primary open-angle glaucoma (POAG) is a chronic and progressive optic nerve condition that results in an acquired loss of optic nerve fibers and potential blindness. The gradual onset of glaucoma results in patients progressively losing their vision without being consciously aware of the changes. Accurate assessment of POAG severity is essential for timely intervention of permanent vision loss. However, ophthalmologists often disagree on severity classification, as individual thresholds for defining severity can vary. Nevertheless, they tend to reach consensus when comparing the relative severity between paired cases. In this work, we propose a framework to compare and interpret the severity of glaucoma using fundus images using siamese-based severity ranking with pairwise n-hidden comparisons. We additionally propose to use pair-wise sailency map to explain why a specific image is deemed more severe than others. Our findings indicate that the proposed severity ranking model surpasses traditional ones in terms of diagnostic accuracy and delivers promising saliency explanations.