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Description

Image Analysis and Machine Learning Platform for Innovation in Diabetic Retinopathy Screening

The North of Portugal Health Administration is implementing a mass screening for diabetic retinopathy (DR). The goal is to perform an eye exam on about 75% of identified diabetics. The goal of the SCREEN-DR consortium is to create a distributed and automatic screening platform for DR, based on PACS management, Machine Learning and Image Analysis, enabling an immediate response from health carers, allowing accurate follow-up strategies, and fostering technological innovation. The main objectives are: automatically assessing image quality, automatically detecting and grading diabetic retinopathy, which can be mild non-proliferative, moderate/severe non-proliferative and proliferative.

Details

Details

  • Acronym

    SCREEN-DR
  • Start

    01st April 2016
  • Global Budget

    552.054,00 €
  • Funded by

Team
news
Networked Intelligent Systems

Original partnership brings together INESC TEC's technology and photographic art

On 23 February, the inauguration of the photography and video exhibition entitled “Olha e Vê. Sente e Vive” and “Outros Retratos e Auto-retratos” (in English “Look and See. Sense and Live” and “Other Portraits and Self-Portraits”) took place at Mira Forum. It was promoted under the project SCREEN-DR of INESC TEC’s Centre for Biomedical Engineering Research (C-BER).

01st March 2019

Networked Intelligent Systems

INESC TEC organises photographic exhibition that combines art and technology

“Olha e Vê. Sente e Vive” and “Outros Retratos e Auto-retratos” (in English “Look and See. Sense and Live” and “Other Portraits and Self-Portraits”) are the captions that map an initiative organised under the project SCREEN-DR, a computational platform for the diabetic retinopathy screening, coordinated by INESC TEC’s Centre for Biomedical Engineering Research (C-BER).

30th January 2019

Networked Intelligent Systems

Article on diabetic retinopathy wins Best Paper Award in the USA

The article "MedAL: Accurate and Robust Deep Active Learning for Medical Image Analysis", in which three INESC TEC’s researchers are co-authors, namely Pedro Costa and Adrian Galdran, collaborators of the Centre for Biomedical Engineering Research (C-BER) on the date of the paper, and Aurélio Campilho, current coordinator of C-BER and Full Professor at the Faculty of Engineering of the University of Porto, received a “best paper award” at ICMLA 2018 - 17th Conference on Machine Learning and Application.

28th January 2019

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Associated Centres

C-BER

Centre

Biomedical Engineering Research

CITE

Centre

Innovation, Technology and Entrepreneurship