Tracking Glaucoma Progression using Deep Learning Methods

My proposed research will develop imaging biomarkers for tracking the progression of glaucoma using deep learning methods. This work will (1) address an urgent need of early detection of glaucoma to reduce chance of irreversible neuron loss, (2) characterize the structural changes in optic disc and reginal nerve fibre layer to build a reference standard for glaucoma diagnosis and grading, and (3) enhance our understanding of the mechanisms of neurodegeneration. My vision is to spearhead new understanding of underlying disease processes in this condition and translate the research outcomes into clinical applications to improve early detection, diagnosis and monitoring of glaucoma.