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We propose a method to predict severity of age related macular degeneration(AMD) from input optical coherence tomography (OCT) images. Although there isno standard clinical severity scale for AMD, we leverage deep learning (DL)based image registration and clustering methods to identify diseased cases andpredict their severity. Experiments demonstrate our approach's diseaseclassification performance matches state of the art methods. The predicteddisease severity performs well on previously unseen data. Registration outputprovides better explainability than class activation maps regarding label andseverity decisions

AMD Severity Prediction And Explainability Using Image Registration And Deep Embedded Clustering