Automated Breast Density Assessment in MRI Using Deep Learning and Radiomics: Strategies for Reducing Inter-Observer Variability.

Journal: Journal of magnetic resonance imaging : JMRI
Published Date:

Abstract

BACKGROUND: Accurate breast density evaluation allows for more precise risk estimation but suffers from high inter-observer variability.

Authors

  • Xueping Jing
    Department of Automation, College of Electrical Engineering and Information Technology, Sichuan University, Chengdu, China.
  • Mirjam Wielema
    Department of Radiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713, GZ, Groningen, The Netherlands.
  • Andrea G Monroy-Gonzalez
    Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
  • Thom R G Stams
    Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
  • Shekar V K Mahesh
    Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
  • Matthijs Oudkerk
    University Medical Center, Groningen, The Netherlands.
  • Paul E Sijens
    Department of Radiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713, GZ, Groningen, The Netherlands.
  • Monique D Dorrius
  • 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.