Establishment of AI-assisted diagnosis of the infraorbital posterior ethmoid cells based on deep learning.

Journal: BMC medical imaging
Published Date:

Abstract

OBJECTIVE: To construct an artificial intelligence (AI)-assisted model for identifying the infraorbital posterior ethmoid cells (IPECs) based on deep learning using sagittal CT images.

Authors

  • Ting Ni
    Department of Radiology, Nanjing Tongren Hospital, School of Medicine, Southeast University, No. 2007, Ji Yin Avenue, Jiang Ning District, Nanjing, 211102, PR China.
  • Xusheng Qian
    School of Electronics and Information Engineering, Soochow University, Suzhou 215006, PR China.
  • Qiang Zeng
    State Key Laboratory of Environment Health (Incubation), Key Laboratory of Environment and Health, Ministry of Education, Key Laboratory of Environment and Health (Wuhan), Ministry of Environmental Protection, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, #13 Hangkong Road, Wuhan, Hubei 430030, China.
  • Yingying Ma
    State Key Laboratory of Chemical Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300072, P. R. China. qiwei@tju.edu.cn.
  • Ziran Xie
    Department of Radiology, Nanjing Tongren Hospital, School of Medicine, Southeast University, No. 2007, Ji Yin Avenue, Jiang Ning District, Nanjing, 211102, PR China.
  • Yakang Dai
    Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu 215163, China. Electronic address: daiyk@sibet.ac.cn.
  • Zigang Che
    Department of Radiology, Nanjing Tongren Hospital, School of Medicine, Southeast University, No. 2007, Ji Yin Avenue, Jiang Ning District, Nanjing, 211102, PR China. chezigang@163.com.