Fully automatic pipeline of convolutional neural networks and capsule networks to distinguish COVID-19 from community-acquired pneumonia via CT images.

Abstract

Authors

• Qianqian Qi
  College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China; Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Northeastern University, Shenyang, China. Electronic address: 386489753@qq.com.
• Shouliang Qi
  Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Life Science Building, 500 Zhihui Street, Hun'nan District, Shenyang, 110169, China. qisl@bmie.neu.edu.cn.
• Yanan Wu
  School of Physics and Optoelectronic Engineering, Ludong University, Yantai, Shandong 264025, China.
• Chen Li
  School of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, China.
• Bin Tian
  Department of Medical Imaging, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, China.
• Shuyue Xia
• Jigang Ren
  Department of Radiology, The Affiliated Hospital of Guizhou Medical University, Guiyang, China.
• Liming Yang
  College of Science, China Agricultural University, 100083, Beijing, China. Electronic address: cauyanglm@163.com.
• Hanlin Wang
  Department of Radiology, General Hospital of the Yangtze River Shipping, Wuhan, China. Electronic address: 75288763@qq.com.
• Hui Yu
  Engineering Technology Research Center of Shanxi Province for Opto-Electric Information and Instrument, Taiyuan 030051, China. 13934603474@nuc.edu.cn.

Keywords

External Resources