Classification of Covid-19 Diseases Through Lung CT-Scan Image Using the ResNet-50 Architecture

Covid-19 is a respiratory tract disease caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The Covid-19 disease was first reported in Wuhan, China, in December 2019. The SARS-CoV-2 virus is primarily transmitted through human contact, and the World Health Organization has pr...

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Bibliographic Details
Published in:Computer engineering and applications journal 2023-02, Vol.12 (1), p.11-30
Main Authors: Kesuma, Lucky Indra, Rudiansyah, Rudiansyah
Format: Article
Language:English
Subjects:
Abnormalities
Accuracy
Artificial neural networks
Classification
Computed tomography
Coronaviruses
COVID-19
Feature extraction
Histograms
Image contrast
Image quality
Lungs
Machine learning
Medical imaging
Pattern recognition
Principal components analysis
Recall
Respiratory diseases
Severe acute respiratory syndrome coronavirus 2
Viral diseases
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Summary:Covid-19 is a respiratory tract disease caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The Covid-19 disease was first reported in Wuhan, China, in December 2019. The SARS-CoV-2 virus is primarily transmitted through human contact, and the World Health Organization has proclaimed a global pandemic (WHO). Symptoms of Covid-19 can range from asymptomatic to mild and severe. One way to diagnose Covid-19 disease can be done by examining lung abnormalities on the results of a Computed Tomography Scan (CT-Scan) of the lungs. However, determining the diagnostic results requires high accuracy and a long time. For this reason, an automated system is needed to make it easier for medical personnel to diagnose Covid-19 disease quickly and accurately. One of the automated systems with computer assistance in detecting abnormalities in CT-Scan images of the lungs is to perform pattern recognition
ISSN:2252-4274
2252-5459
DOI:10.18495/comengapp.v12i1.425