![Esam Abdel-Raheem and doctoral student Sudipta Modak](http://www.uwindsor.ca/dailynews/sites/uwindsor.ca.dailynews/files/styles/full/public/900_esamabdel-raheem_sudiptamodak_1307.jpg?itok=48RUE6ng)
Electrical and computer engineering professor Esam Abdel-Raheem is contributing to a work that is paving the way for early detection of diabetic retinopathy, a leading cause of vision impairment and blindness.
Making an earlier diagnosis will help physicians treat the condition and stave off serious deterioration, says Dr. Abdel-Raheem.
“If this diabetic retinopathy is detected early, over 90 per cent of vision loss can be prevented,” he says. “The current methods of screening rely on manual examinations, which are time-consuming, subjective, and prone to error. Adopting the presented deep learning techniques will result in saving vision and cutting down on overall health-care demands.”
A paper published in IEEE Access, “Deep Learning in Automatic Diabetic Retinopathy Detection and Grading Systems: A Comprehensive Survey and Comparison of Methods,” is co-authored with his doctoral student Sudipta Modak and colleagues from the University of Sharjah, where Abdel-Raheem served as a visiting scholar. This is the first journal article resulting from the collaboration.