Analysis of Separability of COVID-19 and Pneumonia in Chest X-ray Images by Means of Convolutional Neural Networks
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- Investigación (FIC) [1582]
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Analysis of Separability of COVID-19 and Pneumonia in Chest X-ray Images by Means of Convolutional Neural NetworksFecha
2020-08-21Cita bibliográfica
Moura, J.d.; Ramos, L.; Vidal, P.L.; Novo, J.; Ortega, M. Analysis of Separability of COVID-19 and Pneumonia in Chest X-ray Images by Means of Convolutional Neural Networks. Proceedings 2020, 54, 31. https://doi.org/10.3390/proceedings2020054031
Resumen
[Abstract]
The new coronavirus (COVID-19) is a disease that is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). On 11 March 2020, the coronavirus outbreak has been labelled a global pandemic by the World Health Organization. In this context, chest X-ray imaging has become a remarkably powerful tool for the identification of patients with COVID-19 infections at an early stage when clinical symptoms may be unspecific or sparse. In this work, we propose a complete analysis of separability of COVID-19 and pneumonia in chest X-ray images by means of Convolutional Neural Networks. Satisfactory results were obtained that demonstrated the suitability of the proposed system, improving the efficiency of the medical screening process in the healthcare systems.
Palabras clave
Computer-aided diagnosis
Chest X-ray imaging
COVID-19
Pneumonia
Deep learning
Chest X-ray imaging
COVID-19
Pneumonia
Deep learning
Versión del editor
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Atribución 4.0 Internacional
ISSN
2504-3900