Completed Project

SCREEN-DR: Image Analysis and Machine Learning Platform for Innovation in Diabetic Retinopathy Screening



Synopsis / Objectives

Diabetic retinopathy (DR) is the most prevalent microvascular complication of diabetes mellitus and can lead to irreversible visual loss. Screening programs, based on retinal imaging techniques, are fundamental to detect the disease since the initial stages are asymptomatic. Most of these examinations reflect negative cases and many have poor image quality, representing an important inefficiency factor. The SCREEN-DR project aims to tackle this limitation, by researching and developing computer-aided methods for DR.

Main achievements

A research framework for DR ML Classifiers: Evaluation of image quality Detect the non-pathological cases Automatically grade DR in several scales of severity

IEETA Coordinator
IEETA Members

Augusto Silva, Sérgio Matos


CMU, INESC-TEC, ARS-N, CHSJ, BMD, First Solution




April 1, 2016 - December 1, 2020

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