Artificial Intelligence-assisted Retinal Photography
Project Details
Our Artificial Intelligence-driven retinal feature extraction algorithm is applied to live fundus photography to enable computer-aided image aquisition for more effective diabetic retinopathy screening.
This is used to identify potentially ungradable images at the time of aquisition allowing for recapture prior to uploading to a retinopathy grading service or a machine learning retinopathy grading algorithm.
Collaborators
Dr Laima Brazionis, The University of Melbourne