A Deep Neural Network for Detecting Coronavirus Disease Using Chest X-Ray Images

A Deep Neural Network for Detecting Coronavirus Disease Using Chest X-Ray Images

Rajeev Kumar Gupta, Nilesh Kunhare, Rajesh Kumar Pateriya, Nikhlesh Pathik
Copyright: © 2022 |Pages: 27
DOI: 10.4018/IJHISI.20220401.oa1
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Abstract

The novel Covid-19 is one of the leading cause of death worldwide in the year 2020 and declared as a pandemic by world health organization (WHO). This virus affecting all countries across the world and 5 lakh people die as of June 2020 due to Covid-19. Due to the highly contagious nature, early detection of this virus plays a vital role to break Covid chain. Recent studies done by China says that chest CT and X-Ray image may be used as a preliminary test for Covid detection. Deep learning-based CNN model can use to detect Coronavirus automatically from the chest X-rays images. This paper proposed a transfer learning-based approach to detect Covid disease. Due to the less number of Covid chest images, we are using a pre-trained model to classify X-ray images into Covid and Normal class. This paper presents the comparative study of a various pre-trained model like VGGNet-19, ResNet50 and Inception_ResNet_V2. Experiment results show that Inception_ResNet_V2 gives the better result as compare to VGGNet and ResNet model with training and test accuracy of 99.26 and 94, respectively.
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1. Introduction

An outbreak of a new family of the virus in December 2019, SARS- COV-2 (Severe Acute Respiratory Syndrome), has emerged as the leading cause of humans and animal mortality. The impact on public health and the global economy has been devastating. The complicated structure of the virus and zoonotic nature, it is very difficult to diagnosis at early stage. It has claimed more than 10 million lives, including 5 lakh deaths and 4.92 million recovered worldwide (till June 2020), thus compelled WHO to declare COVID -19 as a pandemic in February 2020 (Ozturka T. et al., 2020). Table 1 depicts the top ten coronavirus affected countries in the world.

Table 1.
Distribution of Covid-19 Cases (Top 10 Countries) (as on 27 June 2020)
#CountryTotal CasesTotal DeathsTotal Recovered
World9,987,565498,7335,410,132
1USA2,573,732127,8451,070,367
2Brazil1,280,33556,121697,526
3Russia627,6468,969393,352
4India528,13616,096309,829
5UK310,25043,514N/A
6Spain294,98528,338N/A
7Peru272,3648,939159,806
8Chile267,7665,347228,055
9Italy240,13634,716188,584
10Iran220,18010,364180,661

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