COVID-19 Diagnosis Through Deep Learning Techniques and Chest X-Ray Images

被引：0

作者：

Negreiros R.R.B. ^{[1
,4
]}

Silva I.H.S. ^{[1
]}

Alves A.L.F. ^{[1
,4
]}

Valadares D.C.G. ^{[2
,3
,4
]}

Perkusich A. ^{[2
,4
]}

Baptista C.S. ^{[4
]}

机构：

[1] Federal Institute of Paraíba, Paraíba, Picuí

[2] VIRTUS RDI Center, Paraíba, Campina Grande

[3] Federal Institute of Pernambuco, Pernambuco, Caruaru

[4] Federal University of Campina Grande, Paraíba, Campina Grande

来源：

SN Computer Science | / 4卷 / 5期

关键词：

Artificial intelligence; Image classification; Image diagnosis; Machine learning;

D O I：

10.1007/s42979-023-02043-1

中图分类号：

学科分类号：

摘要：

The new coronavirus pandemic has brought disruption to the world. The lack of mass testing for the population is among the significant dilemmas to be solved by countries, especially underdeveloped ones. An alternative to deal with the lack of tests is detecting the disease by analyzing radiographic images. To process different types of images automatically, we employed deep learning algorithms to achieve success in recognizing different diagnostics. This work aims to train a deep learning model capable of automatically recognizing the COVID-19 diagnosis through radiographic images. Comparing images of coronavirus, healthy lung, and bacterial and viral pneumonia, we obtained a result with 93% accuracy. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

引用

共 58 条

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