Diagnosis of COVID-19 Pneumonia via a Novel Deep Learning Architecture  

作　　者：Xin Zhang Siyuan Lu Shui-Hua Wang Xiang Yu Su-Jing Wang Lun Yao Yi Pan Yu-Dong Zhang 张鑫;陆思源;王水花;余翔;王胜菁;姚仑;潘毅;张煜东(Department of Medical Imaging,The Fourth People's Hospital of Huai'an,Huai'an 223002,China;School of Informatics,University of Leicester,Leicester,LE17RH,U.K.;School of Architecture Building and Civil Engineering,Loughborough University,Loughborough,LE113TU,U.K.;School of Mathematics and Actuarial Science,University of Leicester,Leicester,LE17RH,U.K.;Key Laboratory of Behavior Sciences,Institute of Psychology,Chinese Academy of Sciences,Beijing 100101,China;Department of Psychology,University of the Chinese Academy of Sciences,Beijing 100101,China;Department of Infection Diseases,The Fourth People's Hospital of Huai'an,Huaian 223002,China;Department of Computer Science,Georgia State University,Atlanta 30302-5060,U.S.A.;Department of Information Systems,Faculty of Computing and Information Technology,King Abdulaziz University Jeddah 21589,Saudi Arabia)

机构地区：[1]Department of Medical Imaging,The Fourth People's Hospital of Huai'an,Huai'an 223002,China [2]School of Informatics,University of Leicester,Leicester,LE17RH,U.K. [3]School of Architecture Building and Civil Engineering,Loughborough University,Loughborough,LE113TU,U.K. [4]School of Mathematics and Actuarial Science,University of Leicester,Leicester,LE17RH,U.K. [5]Key Laboratory of Behavior Sciences,Institute of Psychology,Chinese Academy of Sciences,Beijing 100101,China [6]Department of Psychology,University of the Chinese Academy of Sciences,Beijing 100101,China [7]Department of Infection Diseases,The Fourth People's Hospital of Huai'an,Huaian 223002,China [8]Department of Computer Science,Georgia State University,Atlanta 30302-5060,U.S.A. [9]Department of Information Systems,Faculty of Computing and Information Technology,King Abdulaziz University Jeddah 21589,Saudi Arabia

出　　处：《Journal of Computer Science & Technology》2022年第2期330-343,共14页计算机科学技术学报（英文版）

基　　金：supported by the Royal Society International Exchanges Cost Share Award of UK under Grant No.RP202G0230,the Medical Research Council Confidence in Concept Award of UK under Grant No.MC_PC_17171;the Hope Foundation for Cancer Research of UK under Grant No.RM60G0680;the British Heart Foundation Accelerator Award of UK under Grant No.A A/18/3/34220;Sino-UK Industrial Fund under Grant No.RP202G0289;the Global Challenges Research Fund(GCRF)of UK under Grant No.P202PF11;the Fundamental Research Funds for the Central Universities of China under Grant No.CDLS-2020-03;the Key Laboratory of Child Development and Learning Science(Southeast University),Ministry of Education of China,Henan Key Research and Development Project of China,under Grant No.182102310629;the National Natural Science Foundation of China under Grant Nos.U19B2032 and 61772511.

摘　　要：COVID-19 is a contagious infection that has severe effects on the global economy and our daily life.Accurate diagnosis of COVID-19 is of importance for consultants,patients,and radiologists.In this study,we use the deep learning network AlexNet as the backbone,and enhance it with the following two aspects:1)adding batch normalization to help accelerate the training,reducing the internal covariance shift;2)replacing the fully connected layer in AlexNet with three classifiers:SNN,ELM,and RVFL.Therefore,we have three novel models from the deep COVID network(DC-Net)framework,which are named DC-Net-S,DC-Net-E,and DC-Net-R,respectively.After comparison,we find the proposed DC-Net-R achieves an average accuracy of 90.91%on a private dataset(available upon email request)comprising of 296 images while the specificity reaches 96.13%,and has the best performance among all three proposed classifiers.In addition,we show that our DC-Net-R also performs much better than other existing algorithms in the literature.

关 键 词：PNEUMONIA COVID-19 convolutional neural network AlexNet deep learning 

分 类 号：R563.1[医药卫生—呼吸系统] TP181[医药卫生—内科学]