Reprinted from: Publication of this reprint collection is supported by paid advertising SLAS Technology 27 (2022) 63–75 Contents lists available at ScienceDirect SLAS Technology journal homepage: www.elsevier.com/locate/slast Full Length Article COVID-19 detection using chest X-ray images based on a developed deep neural network Zohreh Mousavi a,∗ , Nahal Shahini b , Sobhan Sheykhivand c , Sina Mojtahedi d , Afrooz Arshadi e a Department of Mechanical Engineering, Faculty of Mechanical Engineering, University of Tabriz, Tabriz, Iran bDeparment of Computer Engineering and Information Technology, Amirkabir University of Technology, Tehran, Iran c Department of Biomedical Engineering, Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran dDepartment of Electrical and Electronics Engineering, Faculty of Engineering, Okan University, Istanbul, Turkey e Department of statiatics, Faculty of Mathematical sciences and computer, University of Allameh Tabataba’i, Tehran, Iran a b s t r a c t Aim: Currently, a new coronavirus called COVID-19 is the biggest challenge of the human at 21st century. Now, the spread of this virus is such that mortality has risen strongly in all cities of countries. Therefore, it is necessary to think of a solution to handle the disease by fast and timely diagnosis. This paper proposes a method that uses chest X-ray imagery to divide 2-4 classes into 7 different Scenarios, including Bacterial, Viral, Healthy, and COVID-19 classes. The aim of this study is to propose a method that uses chest X-ray imagery to divide 2-4 classes into 7 different Scenarios, including Bacterial, Viral, Healthy, and COVID-19 classes. Methods: 6 different databases from chest X-ray imagery that have been widely used in recent studies have been gathered for this aim. A Convolutional Neural Network-Long Short Time Memory model is designed and developed to extract features from raw data hierarchically. In order to make more realistic assumptions and use the Proposed Method in the practical field, white Gaussian noise is added to the raw chest X-ray imagery. Additionally, the proposed network is tested and investigated not only on 6 expressed databases but also on two additional databases. Results: On the test set, the proposed network achieved an accuracy of more than 90% for all Scenarios excluding Scenario V, i.e. Healthy against the COVID-19 against the Viral, and also achieved 99% accuracy for separating the COVID-19 from the Healthy group. The results showed that the proposed network is robust to noise up to 1 dB. It is worth noting that the proposed network for two additional databases, which were only used as test databases, also achieved more than 90% accuracy. In addition, in comparison to the state-of-the-art pneumonia detection approaches, the final results obtained from the proposed network is so promising. Conclusions: The proposed network is effective in detecting COVID-19 and other lung infectious diseases using chest X-ray imagery and can thus assist radiologists in making rapid and accurate detections. Introduction The root of the coronavirus word is Greek ( ο ́ ), i.e. crown or halo, which refers to the virus appearance, means Viral infection, under an electron microscope which is similar to a royal crown. That’s why coronavirus is also referred to as the crowned virus [1]. The COVID19 emerged as an epidemic disease in China, Wuhan City, in December 2019. Today, this has altered to a pandemic as a dangerous public health problem all around the world [2]. The COVID-19 also has other names, e.g. SARS-COV-2 virus [3]. This virus is a type of large-family viruses divided into four types including -coronavirus, -coronavirus, -coronavirus, and -coronavirus [4]. To date, seven of the 40 different species in the coronavirus family have been found to be transmitted to humans due to common diseases such as cold [5]. Previous studies have presented that some viruses such as SARS and MERS are transmitted from cats or camels to humans. It is thought that the COVID-19 has been transmitted from anteaters and bats to humans for the first time ∗ Corresponding author. E-mail addresses: zohreh.mousavi@tabrizu.ac.ir (Z. Mousavi), shahini.nahal@aut.ac.ir (N. Shahini), s.sheykhivand@tabrizu.ac.ir (S. Sheykhivand). [5]. Common symptoms of this virus are dry cough, fever, and breath shortness. Also, muscle pain, sputum production, and sore throats are mild symptoms of the COVID-19 [6]. In more serious cases, the virus can cause pneumonia, acute respiratory disorders, septic shock, multiorgan failure, and death [7]. The virus is spread mainly through the tiny droplets of the carrier during coughing. It takes between 2 and 14 days for the virus to develop [7]. The structure of this virus consists of two outer and inner layers. The internal structure of COVID-19 includes the nucleus of the virus that contains genetic material. The outer layer of the virus is made of protein crowns [8]. The virus genome enters the cytoplasm after entering the host cell. According to studies, the incidence of coronavirus in men is higher than in women. Also, children are less likely to get the virus than adults [9]. The mortality rate of COVID-19 is estimated to be between 1% and 5% for children [10]. According to the instructions of hospitalization published by the World Health Organization (WHO) recently, the essence of coronavirus must be verified by Reverse Transcription Polymerase Chain Rehttps://doi.org/10.1016/j.slast.2021.10.011 2472-6303/© 2021 The Authors. Published by Elsevier Inc. on behalf of Society for Laboratory Automation and Screening. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
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