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.

Research Group

Chris Ryan


School Research Themes

Cardiometabolic



Key Contact

For further information about this research, please contact the research group leader.

Department / Centre

Medicine

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