Deep learning-based pulmonary nodule detection: Effect of slab thickness in maximum intensity projections at the nodule candidate detection stage.

Journal: Computer methods and programs in biomedicine
Published Date: Jun 20, 2020

Abstract

BACKGROUND AND OBJECTIVE: To investigate the effect of the slab thickness in maximum intensity projections (MIPs) on the candidate detection performance of a deep learning-based computer-aided detection (DL-CAD) system for pulmonary nodule detection in CT scans.

Authors

  • Sunyi Zheng
  • Xiaonan Cui
    Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Huanhuxi Road, Hexi District, Tianjin 300060, China.
  • Marleen Vonder
    Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
  • Raymond N J Veldhuis
  • Zhaoxiang Ye
    Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Huanhuxi Road, Hexi District, Tianjin 300060, China. Electronic address: yezhaoxiang@163.com.
  • Rozemarijn Vliegenthart
    University of Groningen, University Medical Center Groningen, Department of Radiology, Hanzeplein 1, 9713 GZ Groningen, The Netherlands.
  • Matthijs Oudkerk
    University Medical Center, Groningen, The Netherlands.
  • Peter M A van Ooijen
    University Medical Center Groningen, Center for Medical Imaging - North East Netherlands, University of Groningen, Hanzeplein 1, 9713 GZ, Groningen, The Netherlands.

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