Completed

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

Acronym

SCREEN-DR

Duration

Apr 2016 – Dec 2020

Status

Completed

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.

Results / 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

Partners

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

Project Details

Reference

CMUP-ERI/TIC/0028/2014

Total Funding

126000