Glaucoma Progression Detection and Humphrey Visual Field Prediction Using Discriminative and Generative Vision Transformers

Abstract

Glaucoma is one of the top causes of blindness worldwide. Assessing its progression is critical to determine potential visual impairment and to design sound treatment plans. Standard automated perimetry tests, commonly known as visual field (VF) tests, are clinically used to evaluate the state of functional vision. To provide an accurate and automatic diagnostic tool for clinical decision making in glaucoma progression, we utilize the predictive power of artificial intelligence (AI) and propose two vision transformer (ViT)-based deep learning (DL) networks. First, we optimize a spatiotemporal ViT to classify a subject’s rate of glaucoma progression (GP) using only 3 baseline VFs; we explore ..