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
