Detecção Automática de Doenças Oculares em Imagens de Tomografia de Coerência Óptica

  • Caio H. R. Carvalho UFPI / IFBaiano
  • Antônio M. S. Pinheiro UFPI
  • Rodrigo M. S. Veras UFPI
  • Romuere R. V. Silva UFPI

Resumo


Doenças oculares são problemas oftalmológicos provocados por inúmeros motivos que acarretam, muitas vezes, na cegueira. A Tomografia de Coerência Óptica (OCT) é um exame não-invasivo que permite avaliar possíveis alterações na retina. Este trabalho tem como objetivo a utilização de técnicas de Visão Computacional para o desenvolvimento de modelos de classificação (binária e multiclasse) de anomalias oculares em uma base de imagens de OCT. Os resultados de classificação binária atingiram acurácia entre 97-100% e kappa 93-100%. Os experimentos multiclasse alcançaram acurácia entre 91-92% e kappa entre 86-90%. Os modelos desenvolvidos neste estudo foram promissores na classificação de doenças em imagens de OCT.

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Publicado
27/06/2023
CARVALHO, Caio H. R.; PINHEIRO, Antônio M. S.; VERAS, Rodrigo M. S.; SILVA, Romuere R. V.. Detecção Automática de Doenças Oculares em Imagens de Tomografia de Coerência Óptica. In: SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO APLICADA À SAÚDE (SBCAS), 23. , 2023, São Paulo/SP. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2023 . p. 431-442. ISSN 2763-8952. DOI: https://doi.org/10.5753/sbcas.2023.230144.

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