Detecção de Covid-19 em imagens radiológicas torácicas através da rede neural convolucional (RNC)
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Date
2020-12-11
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Universidade Católica do Salvador
Abstract
The new Covid-19 pandemic, the new coronavirus (SARS-CoV-2), has caused many
problems in several areas of society. Among these problems, the high number of tests
carried out, and the lack of tests, especially in small cities, stands out efficiently. Consid-
ering this insufficient resource in the identification of Covid-19, the objective of this work
was to propose a solution, in an experimental study, to enable the detection of the new
virus using the images of chest radiological medical examinations, which have facilitators
in their realization, such as cost and availability, with the help of an Artificial Intelligence,
more specifically the Convolutional Neural Network (RNC), which they are usually used
to analyze images. The work consisted of its own architecture and a set of 16,500 im-
ages separated into 3 classes (Normal, Covid-19 and Pneumonia), and the results of the
RNC were analyzed and took place on the accuracy of the network algorithms in image
recognition disorders, which is higher than 80 %. The technique proved to be promising
in meeting this demand, in an experimental context. Therefore, it can be indicated as a
complementary instrument in medical diagnosis in the health system for its efficacy and
effectiveness, in addition to the benefits and ease for its implementation, however more
tests are carried out, with a set of wide variables.
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Keywords
Covid-19, Imagens médicas torácicas, Raio-X torácico, Rede neural convolucional, RNC, Inteligência artificial