Exploring the effect of image enhancement techniques on COVID‐19 detection using chest X‐rays images

作     者：Rahman, Tawsifur Khandakar, Amith Qiblawey, Yazan Tahir, Anas Kiranyaz, Serkan Kashem, Saad Bin Abul Islam, Mohammad Tariqul Maadeed, Somaya Al Zughaier, Susu M. Khan, Muhammad Salman Chowdhury, Muhammad E.H. 

作者机构：Department of Biomedical Physics & Technology University of Dhaka Dhaka 1000 Bangladesh Department of Electrical Engineering Qatar University Doha2713 Qatar Faculty of Robotics and Advanced Computing Qatar Armed Forces‐Academic Bridge Program Qatar Foundation Doha24404 Qatar Dept. of Electrical Electronics and Systems Engineering Universiti Kebangsaan Malaysia BangiSelangor43600 Malaysia Department of Computer Science and Engineering Qatar University Doha2713 Qatar Department of Basic Medical Sciences College of Medicine Biomedical and Pharmaceutical Research Unit QU Health Qatar University Doha2713 Qatar  University of Engineering and Technology Peshawar Pakistan 

出 版 物：《arXiv》 (arXiv)

年 卷 期：2020年

核心收录：

主　　题：Image enhancement 

摘      要：The use of computer-aided diagnosis in the reliable and fast detection of corona virus disease (COVID-19) has become a necessity to prevent the spread of the virus during the pandemic to ease the burden on the medical infrastructure. Chest X-ray (CXR) imaging has several advantages over other imaging techniques as it is cheap, easily accessible, fast and portable. CXR images are sometimes of poor quality and so image enhancement techniques can help the machine learning models to extract valuable discriminating features from the image. Numerous works have been reported on COVID-19 detection from smaller set of original X-ray images. However, the effect of image enhancement in COVID-19 detection was not reported in the literature. This paper explores the effect of various popular image enhancement techniques and states the © 2020, CC BY.