The Deep Neural Network Approach Model forDetecting Covid-19 from X-Ray Scans of Chest

DOI

No DOI

Published In

Volume 3, Issue 3 (2022)

Published Online

May-June 2022

Pages

618-622

Article Type

Research Article

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Abstract: In the presence of the current context of the global pandemic COVID- 19 and limitations of the current testing methods like RT-PCR and antigen. Early diagnosis of the Severe Acute Respiratory Syndrome Corona Virus-2 (SARS-CoV- 2), and clinical expertise, allow institutes and governments to break the chain of transmission and flatten the pandemic curve. We propose the deep learning model to detect the infection of COVID-19 or other lung infections present in lung-like lung cancer or pneumonia and also plot the region of covid presence in the lungs using a heatmap. Although reverse transcription-polymerase chain reaction(RT-PCR) offers quick results, chest X-ray (CXR) imaging is a more reliable method of disease classification and assessment. Recent studies that are conducted afterthe COVID-19 rapid spread have confirmed the Convolution Neural Networks (CNN) of the Deep Learning approach. The data includes chest X-rays (CXR) of themedical schools of Germany, Europe, India and the United States of America (USA) and the radiological society of North America and BIMCV (Medical ImagingDatabase of Valencia Region). This paper aims to facilitate experts (medical or otherwise) and technicians in understanding the ways deep learning techniques are used in this regard and how they can be potentially further utilized to combat the outbreak of COVID-19.