CT-FastNet: Detecção de COVID-19 a partir de Tomografias Computadorizadas (TC) de Tórax usando Inteligência Artificial/ CT-FastNet: Detection of COVID-19 From Chest Computed Tomography (CT) Images Using Artificial Intelligence

Authors

  • Rodrigo Carvalho Barbosa
  • Renata Lopes Rosa
  • Kátia Cilene Neles da Silva
  • Demostenes Zegarra Rodriguez

DOI:

https://doi.org/10.34117/bjdv6n7-619

Keywords:

COVID-19, Redes Neurais Artificiais, Tomografia Computadorizada (TC) de Tórax.

Abstract

Many countries have been affected by the COVID-19, and health departments are facing delays to detect the new coronavirus symptoms. Artificial Intelligence (AI) models are designed for the automatic detection of respiratory diseases patterns using computed tomography (CT) scans of the chest. However, the training time consumed by the algorithms is a key parameter that is not properly attended. In this article, we propose an AI solution using an activation function that helps to obtain a low training time. Experimental results show that our proposal overcome several deep learning architectures, such as the 3D deep Convolutional Neural Network to Detect COVID-19 (DeCoVNet).

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Published

2020-07-23

How to Cite

Barbosa, R. C., Rosa, R. L., Silva, K. C. N. da, & Rodriguez, D. Z. (2020). CT-FastNet: Detecção de COVID-19 a partir de Tomografias Computadorizadas (TC) de Tórax usando Inteligência Artificial/ CT-FastNet: Detection of COVID-19 From Chest Computed Tomography (CT) Images Using Artificial Intelligence. Brazilian Journal of Development, 6(7), 50315–50330. https://doi.org/10.34117/bjdv6n7-619

Issue

Section

Original Papers