Identifying pulmonary nodules or masses on chest radiography using deep learning: external validation and strategies to improve clinical practice.

Journal: Clinical radiology
Published Date: Sep 11, 2019

Abstract

AIM: To test the diagnostic performance of a deep learning-based system for the detection of clinically significant pulmonary nodules/masses on chest radiographs.

Authors

  • C-H Liang
    Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming University, Taipei, Taiwan; Faculty of Medicine, School of Medicine, National Yang Ming University, Taipei, Taiwan; Institute of Clinical Medicine, National Yang Ming University, Taipei, Taiwan.
  • Y-C Liu
    Department of Diagnostic Radiology, Xiamen Chang Gung Hospital, China.
  • M-T Wu
    Faculty of Medicine, School of Medicine, National Yang Ming University, Taipei, Taiwan; Institute of Clinical Medicine, National Yang Ming University, Taipei, Taiwan; Department of Radiology, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan.
  • F Garcia-Castro
    Radiology Department, Hospital Universitarioy Polite'cnico La Fe and Biomedical Imaging Research Group (GIBI230), Valencia, Spain; QUIBIM SL, Valencia, Spain.
  • A Alberich-Bayarri
    Radiology Department, Hospital Universitarioy Polite'cnico La Fe and Biomedical Imaging Research Group (GIBI230), Valencia, Spain; QUIBIM SL, Valencia, Spain.
  • F-Z Wu
    Faculty of Medicine, School of Medicine, National Yang Ming University, Taipei, Taiwan; Institute of Clinical Medicine, National Yang Ming University, Taipei, Taiwan; Department of Radiology, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan. Electronic address: cmvwu1029@gmail.com.

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