Deep learning-assisted prostate cancer detection on bi-parametric MRI: minimum training data size requirements and effect of prior knowledge.

Journal: European radiology
Published Date: Apr 1, 2022

Abstract

OBJECTIVES: To assess Prostate Imaging Reporting and Data System (PI-RADS)-trained deep learning (DL) algorithm performance and to investigate the effect of data size and prior knowledge on the detection of clinically significant prostate cancer (csPCa) in biopsy-naïve men with a suspicion of PCa.

Authors

  • Matin Hosseinzadeh
  • Anindo Saha
    Diagnostic Image Analysis Group, Department of Medical Imaging, Radboudumc, Nijmegen, The Netherlands.
  • Patrick Brand
    Diagnostic Image Analysis Group, Department of Medical Imaging, Radboudumc, Nijmegen, The Netherlands.
  • Ilse Slootweg
    Diagnostic Image Analysis Group, Department of Medical Imaging, Radboudumc, Nijmegen, The Netherlands.
  • Maarten de Rooij
    Department of Medical Imaging, Radboud university medical center, P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands.
  • Henkjan Huisman
    Department of Radiology and Nuclear Medicine, Radboud University Medical Center, Nijmegen, The Netherlands.

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