A Cascaded Deep Learning-Based Artificial Intelligence Algorithm for Automated Lesion Detection and Classification on Biparametric Prostate Magnetic Resonance Imaging.

Journal: Academic radiology
Published Date: Sep 28, 2021

Abstract

RATIONALE AND OBJECTIVES: Prostate MRI improves detection of clinically significant prostate cancer; however, its diagnostic performance has wide variation. Artificial intelligence (AI) has the potential to assist radiologists in the detection and classification of prostatic lesions. Herein, we aimed to develop and test a cascaded deep learning detection and classification system trained on biparametric prostate MRI using PI-RADS for assisting radiologists during prostate MRI read out.

Authors

  • Sherif Mehralivand
    Molecular Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
  • Dong Yang
    College of Chemistry and Chemical Engineering, Shaanxi University of Science and Technology Xi'an 710021 China yangdong@sust.edu.cn.
  • Stephanie A Harmon
    Clinical Research Directorate, Frederick National Laboratory for Cancer Research sponsored by the National Cancer Institute, Frederick, Maryland, USA.
  • Daguang Xu
    NVIDIA, Santa Clara, CA, USA.
  • Ziyue Xu
    Center for Infectious Disease Imaging (CIDI), Radiology and Imaging Science Department, National Institutes of Health (NIH), Bethesda, MD 20892, United States.
  • Holger Roth
    Graduate School of Informatics, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, 464-8601, Japan.
  • Samira Masoudi
    Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
  • Thomas H Sanford
    State University of New York-Upstate Medical Center, Syracuse, NY, USA.
  • Deepak Kesani
    Molecular Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
  • Nathan S Lay
    Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, 10 Center Dr., MSC 1182, Building 10, Room B3B85, Bethesda, Maryland.
  • Maria J Merino
    Center for Interventional Oncology, National Cancer Institute & Clinical Center, National Institutes of Health, Bethesda, MD, USA.
  • Bradford J Wood
    Molecular Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
  • Peter A Pinto
    Urologic Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
  • Peter L Choyke
    Molecular Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
  • Baris Turkbey
    Molecular Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.

Keywords

External Resources

Popular Topics
Recent Journals