SCREEN-DR: Image Analysis and Machine Learning Platform for Innovation in Diabetic Retinopathy Screening
"SCREEN-DR initiative creates the great opportunity to translate diverse and cooperating information technology expertise in two Portuguese Universities and Carnegie Mellon University to both clinical practice and entrepreneurial world, in a challenging health worldwide problem of Diabetic Retinopathy, in a multicentre mass screening environment." Aurélio Campilho and Gustavo Rohde
(INESC TEC; FEUP)
Research teams: Carnegie Mellon University (CMU); Instituto de Engenharia de Sistemas e Computadores, Tecnologia e Ciência (INESC TEC); Universidade de Aveiro (UA)
Organizations: Administração Regional de Saúde do Norte (ARSN); BMD Software (BMD); Centro Hospitalar do Tâmega e Sousa (CHTS); First Solutions; Hospital de São João (HSJ); University of Pittsburgh Medical Center, USA (UPMC)
Main Research Unit: Instituto de Engenharia de Sistemas e Computadores, Tecnologia e Ciência (INESC TEC)
Funding Reference: CMUP-ERI/TIC/0028/2014
Duration: 48 months
Keywords: Medical image analysis; Computer-aided diagnosis; Collaborative PACS-Cloud; Diabetic retinopathy screening
Diabetic Retinopathy (DR) is a leading
cause of blindness in the industrialized world that can be avoided with early
treatment, demanding an earlier diagnosis in a stage where the treatment is
still possible and effective. DR evolves silently without any visual symptoms,
during the early stages of the disease.
The Portuguese North Health Administration
(ARSN) is implementing a mass screening for DR, with the goal of making eye
exam of about 75% of identified diabetics, from an estimated diabetic
population of 250.000, in the North of Portugal.
SCREEN-DR is the platform to be developed
in this project to face three main challenges. The first challenge is to
automatically evaluate image quality, and consequent removal the low quality
images from the workflow. The second is to automatically detect the
non-pathological cases. If these two challenges are overcome, the
ophthalmologists need to analyze only about 25% of the cases, which will be an
important gain in terms of time-to-decision and efficacy. Additionally, the
third challenge is to automatically grade DR in several scales of the disease
severity. Each one of these challenges corresponds to an image module that will
be remotely accessible by an image web service.
Under this context, the vision of the
consortium SCREEN-DR is to create a distributed and automatic screening
platform for DR, based on the state-of-the-art Information and Communication
Technologies (ICT), including advanced Picture Archiving and Communication
Systems (PACS) management, Machine Learning and Image Analysis, enabling
immediate response from health carers, allowing accurate follow-up strategies,
and fostering technological innovation.
The Phase II of the Carnegie Mellon Portugal Program emphasizes advanced
education and research that can lead to significant entrepreneurial
impact. The activities of the program are for the most part configured
in Entrepreneurial Research Initiatives (ERIs).
Research Opportunities more