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Project details


FILTER – Framework to Develop and Validate Automated Image Analysis Systems for Early Diagnosis and Treatment of Eyes at Risk in Blinding Age-Related Disease

Age-related macular degeneration (AMD), diabetic retinopathy (DR) and Glaucoma are the leading causes of vision loss worldwide. The two primary risk factors for these diseases are aging and lifestyle. Diabetic retinopathy is the leading cause of blindness in the working population of developed countries, and age-related macular degeneration is the main cause of irreversible blindness in developed nations among individuals older than 65 years of age. It is estimated that the numbers of people with these diseases will increase due to the aging of the population. In Portugal, there are 2.105.167 citizens over 65+ years, 521.212 in the Centro Region (2014, Instituto Nacional de Estatística) and these numbers are expected to increase.

Evidence demonstrates that early diagnosis and treatment of AMD , DR and glaucoma are vital to prevent or delay disease progression (Chew & Schachat 2015). These conditions tend to be asymptomatic in the early stages but in the later stages lead to severe visual impairments. Despite the recommendations for annual ophthalmic screening for diabetic patients and annual or biennial ophthalmic screening for all individuals 65 years or older, a high number of people are unaware of their disease condition. It is, therefore, urgent to reduce the number of undiagnosed individuals. The most conventional methods (face-to-face appointments with an eye specialist) may pose an economic problem to the health system, and telemedicine has emerged as an alternative method. In fact, DR , AMD and Glaucoma can be diagnosed visually via several imaging techniques, with clear advantages (cost-effective (Chew & Schachat 2015), simple to operate, readily available, and patient friendly). Also, telemedicine constitutes an efficient means to overcome the lack of ophthalmologists in primary health care centers. Therefore, new strategies should be developed to diagnosis, thus alleviating the burden on the National Health Service.


Rufino Silva


July 2018


CNTM - Centre of New Technologies for Medicine


https://www.aibili.pt/projects_filter.php


Research Team

Catarina Neves

Cláudia Farinha

Conceição Lobo

José Cunha-Vaz

Luis Guilherme Mendes

Maria Luísa Ribeiro

Telmo Miranda

Torcato Santos

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