Classificação de Nódulos Pulmonares Utilizando Redes Neurais Convolucionais 3D

  • Thiago Lima UFPI
  • Daniel Luz UFPI
  • Rodrigo Veras UFPI
  • Flavio Araújo UFPI

Resumo


O câncer de pulmão é o segundo mais comum no Brasil. A detecção precoce de nódulos pulmonares é essencial para a sobrevivência do paciente. Neste trabalho propomos um algoritmo baseado na Rede Neural Convolucional 3D para classificar nódulos pulmonares como benignos ou malignos em imagens da tomografia computadorizada. A arquitetura proposta possui dois blocos de camadas convolucionais seguidos por uma camada de pooling, duas camadas totalmente conectadas e uma softmax. O uso de aumento de dados para balanceamento do conjunto de treino produziu resultados promissores, com acurácia de 0,9077, kappa de 0,7774, sensibilidade de 0,8481, especificidade de 0,9322 e AUC de 0,8901, na classificação de nódulos pulmonares.

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Publicado
15/09/2020
LIMA, Thiago; LUZ, Daniel; VERAS, Rodrigo ; ARAÚJO, Flavio. Classificação de Nódulos Pulmonares Utilizando Redes Neurais Convolucionais 3D. In: SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO APLICADA À SAÚDE (SBCAS), 20. , 2020, Evento Online. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2020 . p. 120-130. ISSN 2763-8952. DOI: https://doi.org/10.5753/sbcas.2020.11507.