Journal ArticleUnknown
COVID-19 infection localization and severity grading from chest X-ray images
Authors
Author Affiliations
Qatar University, Bangladesh University of Engineering and Technology, Hamad General Hospital, Weill Cornell Medical College in Qatar
Published InQatar University QSpace (Qatar University)
Year2022
Citations194
Abstract
The immense spread of coronavirus disease 2019 (COVID-19) has left healthcare systems incapable to diagnose and test patients at the required rate. Given the effects of COVID-19 on pulmonary tissues, chest radiographic imaging has become a necessity for screening and monitoring the disease. Numerous studies have proposed Deep Learning approaches for the automatic diagnosis of COVID-19. Although these methods achieved outstanding performance in detection, they have used limited chest X-ray (CXR) repositories for evaluation, usually with a few hundred COVID-19 CXR images only. Thus, such data scarcity prevents reliable evaluation of Deep Learning models with the potential of overfitting. In addition, most studies showed no or limited capability in infection localization and severity grading of COVID-19 pneumonia. In this study,…
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