Pulse Sequence Dependence of a Simple and Interpretable Deep Learning Method for Detection of Clinically Significant Prostate Cancer Using Multiparametric MRI.

Journal: Academic radiology
Published Date:

Abstract

RATIONALE AND OBJECTIVES: Multiparametric magnetic resonance imaging (mpMRI) is increasingly used for risk stratification and localization of prostate cancer (PCa). Thanks to the great success of deep learning models in computer vision, the potential application for early detection of PCa using mpMRI is imminent.

Authors

  • Heejong Kim
    Nokia Bell Labs, New Providence, New Jersey 07974 United States.
  • Daniel J A Margolis
    Department of Radiology, Weill Cornell Medicine, New York, NY, USA. Electronic address: djm9016@med.cornell.edu.
  • Himanshu Nagar
    Department of Radiation Oncology, Weill Cornell Medical College, New York, New York, USA.
  • Mert R Sabuncu
    Department of Radiology, Weill Cornell Medicine, New York, NY, USA.