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
Research Group
School Research Themes
Key Contact
For further information about this research, please contact the research group leader.
Department / Centre
MDHS Research library
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