Detection of pulmonary ground-glass opacity based on deep learning computer artificial intelligence.

Abstract

Authors

• Wenjing Ye
  Department of Respiratory Medicine, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200092, China.
• Wen Gu
  Department of Respiratory Medicine, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200092, China.
• Xuejun Guo
  Department of Respiratory Medicine, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200092, China. guoxuejun@xinhuamed.com.cn.
• Ping Yi
  School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China. yiping@sjtu.edu.cn.
• Yishuang Meng
  School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
• Fengfeng Han
  Department of Respiratory Medicine, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200092, China.
• Lingwei Yu
  Department of Radiology, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200092, China.
• Yi Chen
  Department of Anesthesiology and Perioperative Medicine, General Hospital of Ningxia Medical University, Yinchuan, China.
• Guorui Zhang
  Department of Respiratory Medicine, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200092, China.
• Xueting Wang
  Shanghai Jiaotong University School of Medicine, Shanghai, 200092, China.

Keywords

External Resources