A new approach for classifying coronavirus COVID-19 based on its manifestation on chest X-rays using texture features and neural networks.
Inf Sci (N Y)
; 545: 403-414, 2021 Feb 04.
Article
em En
| MEDLINE
| ID: mdl-32999505
Since the recent challenge that humanity is facing against COVID-19, several initiatives have been put forward with the goal of creating measures to help control the spread of the pandemic. In this paper we present a series of experiments using supervised learning models in order to perform an accurate classification on datasets consisting of medical images from COVID-19 patients and medical images of several other related diseases affecting the lungs. This work represents an initial experimentation using image texture feature descriptors, feed-forward and convolutional neural networks on newly created databases with COVID-19 images. The goal was setting a baseline for the future development of a system capable of automatically detecting the COVID-19 disease based on its manifestation on chest X-rays and computerized tomography images of the lungs.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Idioma:
En
Revista:
Inf Sci (N Y)
Ano de publicação:
2021
Tipo de documento:
Article
País de afiliação:
México
País de publicação:
Estados Unidos