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Screening of diabetic retinopathy

Full title: Automatic screening of diabetic retinopathy by artificial intelligence.

Project period

Start: October 2017
End: 30 September 2028


The study aims to develop a software system that utilises deep-learning by fully convolutional networks (FCN) in order to perform automatic grading of retinal images to detect diabetic retinopathy (DR). This will be achieved through two main objectives:

  1. Utilising more than 35,000 retinal images obtained at Odense University Hospital (OUH), we will firstly train an FCN to recognise characteristic DR lesions.
  2. Secondly, we will validate this in a subset of images in order to facilitate automatic DR-grading.



The project has received support from PhD scholarships from Steno Diabetes Center Odense and Helse Sør-Øst in Norway.

The project is part of an ongoing collaboration between the Department of Ophtalmology at Odense University Hospital, Steno Diabetes Center Odense and the group of Professor Thiusius Rajeeth Savarimuthu at the Maersk Mc-Kinney Moller Institute, University of Southern Denmark. 

Additional studies include studies regarding deep-learning-based identification in patients with sight-threatening diabetic retinopathy and the use of artificial intelligence to facilitate grading skills in the virtual ocular learning platform VIOLA.

Jakob Grauslund

Jakob Grauslund

Professor, Chief Physician

Odense University Hospital, Department of Ophthalmology

(+45) 6541 2782
Thiusius Rajeeth Savarimuthu

Thiusius Rajeeth Savarimuthu

Research Manager - Professor

Centre for Clinical Robotics (CCR). University of Southern Denmark, Maersk Mc-Kinney Moller Institute

(+45) 24 40 95 45