Using X-ray Images and Deep Learning for Automated Detection of Coronavirus Disease

Overview

Journal J Biomol Struct Dyn

Specialties Biochemistry
Molecular Biology

Date 2020 May 14

PMID 32397844

Citations 105

Authors

Khalid El Asnaoui

Youness Chawki

Affiliations

Soon will be listed here.

Abstract

Coronavirus is still the leading cause of death worldwide. There are a set number of COVID-19 test units accessible in emergency clinics because of the expanding cases daily. Therefore, it is important to implement an automatic detection and classification system as a speedy elective finding choice to forestall COVID-19 spreading among individuals. Medical images analysis is one of the most promising research areas, it provides facilities for diagnosis and making decisions of a number of diseases such as Coronavirus. This paper conducts a comparative study of the use of the recent deep learning models (VGG16, VGG19, DenseNet201, Inception_ResNet_V2, Inception_V3, Resnet50, and MobileNet_V2) to deal with detection and classification of coronavirus pneumonia. The experiments were conducted using chest X-ray & CT dataset of 6087 images (2780 images of bacterial pneumonia, 1493 of coronavirus, 231 of Covid19, and 1583 normal) and confusion matrices are used to evaluate model performances. Results found out that the use of inception_Resnet_V2 and Densnet201 provide better results compared to other models used in this work (92.18% accuracy for Inception-ResNetV2 and 88.09% accuracy for Densnet201).Communicated by Ramaswamy H. Sarma.

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References

Li Q, Guan X, Wu P, Wang X, Zhou L, Tong Y . Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia. N Engl J Med. 2020; 382(13):1199-1207. PMC: 7121484. DOI: 10.1056/NEJMoa2001316. View

Ghosh A, Gupta R, Misra A . Telemedicine for diabetes care in India during COVID19 pandemic and national lockdown period: Guidelines for physicians. Diabetes Metab Syndr. 2020; 14(4):273-276. PMC: 7129346. DOI: 10.1016/j.dsx.2020.04.001. View

Aanouz I, Belhassan A, El-Khatabi K, Lakhlifi T, El-Ldrissi M, Bouachrine M . Moroccan Medicinal plants as inhibitors against SARS-CoV-2 main protease: Computational investigations. J Biomol Struct Dyn. 2020; 39(8):2971-2979. PMC: 7212546. DOI: 10.1080/07391102.2020.1758790. View

Wahedi H, Ahmad S, Abbasi S . Stilbene-based natural compounds as promising drug candidates against COVID-19. J Biomol Struct Dyn. 2020; 39(9):3225-3234. DOI: 10.1080/07391102.2020.1762743. View

Sharifi-Razavi A, Karimi N, Rouhani N . COVID-19 and intracerebral haemorrhage: causative or coincidental?. New Microbes New Infect. 2020; 35:100669. PMC: 7163302. DOI: 10.1016/j.nmni.2020.100669. View

Ng M, Lee E, Yang J, Yang F, Li X, Wang H . Imaging Profile of the COVID-19 Infection: Radiologic Findings and Literature Review. Radiol Cardiothorac Imaging. 2021; 2(1):e200034. PMC: 7233595. DOI: 10.1148/ryct.2020200034. View

Sarma P, Shekhar N, Prajapat M, Avti P, Kaur H, Kumar S . In-silico homology assisted identification of inhibitor of RNA binding against 2019-nCoV N-protein (N terminal domain). J Biomol Struct Dyn. 2020; 39(8):2724-2732. PMC: 7256351. DOI: 10.1080/07391102.2020.1753580. View

Elmezayen A, Al-Obaidi A, Sahin A, Yelekci K . Drug repurposing for coronavirus (COVID-19): screening of known drugs against coronavirus 3CL hydrolase and protease enzymes. J Biomol Struct Dyn. 2020; 39(8):2980-2992. PMC: 7189413. DOI: 10.1080/07391102.2020.1758791. View

Islam R, Parves M, Paul A, Uddin N, Rahman M, Mamun A . A molecular modeling approach to identify effective antiviral phytochemicals against the main protease of SARS-CoV-2. J Biomol Struct Dyn. 2020; 39(9):3213-3224. PMC: 7232885. DOI: 10.1080/07391102.2020.1761883. View

10.

Khan R, Jha R, Amera G, Jain M, Singh E, Pathak A . Targeting SARS-CoV-2: a systematic drug repurposing approach to identify promising inhibitors against 3C-like proteinase and 2'-O-ribose methyltransferase. J Biomol Struct Dyn. 2020; 39(8):2679-2692. PMC: 7189412. DOI: 10.1080/07391102.2020.1753577. View

11.

Huang P, Liu T, Huang L, Liu H, Lei M, Xu W . Use of Chest CT in Combination with Negative RT-PCR Assay for the 2019 Novel Coronavirus but High Clinical Suspicion. Radiology. 2020; 295(1):22-23. PMC: 7233360. DOI: 10.1148/radiol.2020200330. View

12.

Das S, Sarmah S, Lyndem S, Singha Roy A . An investigation into the identification of potential inhibitors of SARS-CoV-2 main protease using molecular docking study. J Biomol Struct Dyn. 2020; 39(9):3347-3357. PMC: 7232884. DOI: 10.1080/07391102.2020.1763201. View

13.

Al-Masni M, Al-Antari M, Park J, Gi G, Kim T, Rivera P . Simultaneous detection and classification of breast masses in digital mammograms via a deep learning YOLO-based CAD system. Comput Methods Programs Biomed. 2018; 157:85-94. DOI: 10.1016/j.cmpb.2018.01.017. View

14.

Ruuska S, Hamalainen W, Kajava S, Mughal M, Matilainen P, Mononen J . Evaluation of the confusion matrix method in the validation of an automated system for measuring feeding behaviour of cattle. Behav Processes. 2018; 148:56-62. DOI: 10.1016/j.beproc.2018.01.004. View

15.

Lee A, Morling J . COVID19: The need for public health in a time of emergency. Public Health. 2020; 182:188-189. PMC: 7141551. DOI: 10.1016/j.puhe.2020.03.027. View

16.

Enayatkhani M, HasaniAzad M, Faezi S, Gouklani H, Davoodian P, Ahmadi N . Reverse vaccinology approach to design a novel multi-epitope vaccine candidate against COVID-19: an study. J Biomol Struct Dyn. 2020; 39(8):2857-2872. PMC: 7196925. DOI: 10.1080/07391102.2020.1756411. View

17.

Roosa K, Lee Y, Luo R, Kirpich A, Rothenberg R, Hyman J . Real-time forecasts of the COVID-19 epidemic in China from February 5th to February 24th, 2020. Infect Dis Model. 2020; 5:256-263. PMC: 7033348. DOI: 10.1016/j.idm.2020.02.002. View

18.

Sinha S, Shakya A, Prasad S, Singh S, Gurav N, Prasad R . An evaluation of different Saikosaponins for their potency against SARS-CoV-2 using NSP15 and fusion spike glycoprotein as targets. J Biomol Struct Dyn. 2020; 39(9):3244-3255. PMC: 7232888. DOI: 10.1080/07391102.2020.1762741. View

19.

Liu R, Han H, Liu F, Lv Z, Wu K, Liu Y . Positive rate of RT-PCR detection of SARS-CoV-2 infection in 4880 cases from one hospital in Wuhan, China, from Jan to Feb 2020. Clin Chim Acta. 2020; 505:172-175. PMC: 7094385. DOI: 10.1016/j.cca.2020.03.009. View

20.

Enmozhi S, Raja K, Sebastine I, Joseph J . Andrographolide as a potential inhibitor of SARS-CoV-2 main protease: an in silico approach. J Biomol Struct Dyn. 2020; 39(9):3092-3098. PMC: 7212536. DOI: 10.1080/07391102.2020.1760136. View