Artificial Intelligence-assisted Retinal Photography

Project Details

fundus image feautre extraction

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.


Dr Laima Brazionis, The University of Melbourne

Research Group

Chris Ryan Laima Brazionis

School Research Themes


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