Performance of Deep Learning and Genitourinary Radiologists in Detection of Prostate Cancer Using 3-T Multiparametric Magnetic Resonance Imaging.

Journal: Journal of magnetic resonance imaging : JMRI
Published Date: Mar 12, 2021

Abstract

BACKGROUND: Several deep learning-based techniques have been developed for prostate cancer (PCa) detection using multiparametric magnetic resonance imaging (mpMRI), but few of them have been rigorously evaluated relative to radiologists' performance or whole-mount histopathology (WMHP).

Authors

  • Ruiming Cao
  • Xinran Zhong
  • Sohrab Afshari
    Department of Radiology, UCLA, Los Angeles, California, USA.
  • Ely Felker
    Department of Radiology, UCLA, Los Angeles, California, USA.
  • Voraparee Suvannarerg
    Department of Radiology, UCLA, Los Angeles, California, USA.
  • Teeravut Tubtawee
    Division of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  • Sitaram Vangala
    Department of Medicine Statistics Core, UCLA, Los Angeles, California, USA.
  • Fabien Scalzo
  • Steven Raman
  • Kyunghyun Sung
    Department of Radiological Sciences, University of California Los Angeles, Los Angeles, California.

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