Human-recognizable CT image features of subsolid lung nodules associated with diagnosis and classification by convolutional neural networks.

Journal: European radiology
Published Date: Apr 13, 2021

Abstract

OBJECTIVES: The interpretability of convolutional neural networks (CNNs) for classifying subsolid nodules (SSNs) is insufficient for clinicians. Our purpose was to develop CNN models to classify SSNs on CT images and to investigate image features associated with the CNN classification.

Authors

  • Beibei Jiang
    Radiology Department, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Haining Rd.100, Shanghai, 200080 China.
  • Yaping Zhang
    Radiology Department, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Haining Rd.100, Shanghai, 200080 China.
  • Lu Zhang
    Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX, United States.
  • Geertruida H de Bock
    Department of Epidemiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ, Groningen, The Netherlands.
  • Rozemarijn Vliegenthart
    University of Groningen, University Medical Center Groningen, Department of Radiology, Hanzeplein 1, 9713 GZ Groningen, The Netherlands.
  • Xueqian Xie
    Radiology Department, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Haining Rd.100, Shanghai, 200080 China.

Keywords

External Resources

Popular Topics
Recent Journals