Classification of chest X-ray images using Machine Learning and Histogram of Oriented Gradients

  • Fellipe M. C. Barbosa UFRN
  • Anne Magaly de P. Canuto UFRN

Resumo


Este trabalho propõe um modelo de aprendizado de máquina para classificar e detectar a presença de pneumonia a partir de uma coleção de amostras de radiografias do tórax. Ao contrário da maioria dos trabalhos que utilizam abordagens de aprendizado profundo para classificar se a imagem é de um pulmão com pneumonia ou não, ou seja, duas classes para assim alcançar um desempenho de classificação notável, este modelo utiliza Histograma de Gradientes Orientados para extrair características de uma determinada imagem de raio-X de tórax e classificá-la em três classes, determinando se uma pessoa está ou não infectada com pneumonia viral ou bacteriana. Apesar de uma maior complexidade e utilização de modelos tradicionais de aprendizado de máquina, a maior acurácia alcançada foi de 91.32% superior a de trabalhos que utilizam redes profundas e buscam resolver o mesmo grau de complexidade.

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Publicado
29/11/2021
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BARBOSA, Fellipe M. C.; CANUTO, Anne Magaly de P.. Classification of chest X-ray images using Machine Learning and Histogram of Oriented Gradients. In: ENCONTRO NACIONAL DE INTELIGÊNCIA ARTIFICIAL E COMPUTACIONAL (ENIAC), 18. , 2021, Evento Online. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2021 . p. 49-58. DOI: https://doi.org/10.5753/eniac.2021.18240.