Automatic Detection of COVID-19 from Chest X-ray Images with Convolutional Neural Networks

Khandaker Foysal Haque, Fatin Farhan Haque, Lisa Gandy, Ahmed Abdelgawad

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

22 Scopus citations

Abstract

Deep Learning has improved multi-fold in recent years and it has been playing a great role in image classification which also includes medical imaging. Convolutional Neural Networks (CNN) has been performing well in detecting many diseases including Coronary Artery Disease, Malaria, Alzheimer's disease, different dental diseases, and Parkinson's disease. Like other cases, CNN has a substantial prospect in detecting COVID-19 patients with medical images like chest X-rays and CTs. Coronavirus or COVID-19 has been declared a global pandemic by the World Health Organization (WHO). Till July 11, 2020, the total COVID-19 confirmed cases are 12.32 M and deaths are 0.556 M worldwide. Detecting Corona positive patients is very important in preventing the spread of this virus. On this conquest, a CNN model is proposed to detect COVID-19 patients from chest X-ray images. This model is evaluated with a comparative analysis of two other CNN models. The proposed model performs with an accuracy of 97.56% and a precision of 95.34%. This model gives the Receiver Operating Characteristic (ROC) curve area of 0.976 and F1-score of 97.61. It can be improved further by increasing the dataset for training the model.

Original languageEnglish
Title of host publicationProceedings - 2020 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2020
EditorsMahdi H. Miraz, Peter S. Excell, Andrew Ware, Safeeullah Soomro, Maaruf Ali
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages125-130
Number of pages6
ISBN (Electronic)9781728163307
DOIs
StatePublished - Aug 17 2020
Event3rd International Conference on Computing, Electronics and Communications Engineering, iCCECE 2020 - Virtual, Southend, United Kingdom
Duration: Aug 17 2020Aug 18 2020

Publication series

NameProceedings - 2020 International Conference on Computing, Electronics and Communications Engineering, iCCECE 2020

Conference

Conference3rd International Conference on Computing, Electronics and Communications Engineering, iCCECE 2020
Country/TerritoryUnited Kingdom
CityVirtual, Southend
Period08/17/2008/18/20

Keywords

  • CNN
  • COVID-19
  • COVID-19 Detection
  • Coronavirus
  • Deep Learning

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