Deep learning for automated exclusion of cardiac CT examinations negative for coronary artery calcium.

Journal: European journal of radiology
Published Date: Aug 1, 2020

Abstract

PURPOSE: Coronary artery calcium (CAC) score has shown to be an accurate predictor of future cardiovascular events. Early detection by CAC scoring might reduce the number of deaths by cardiovascular disease (CVD). Automatically excluding scans which test negative for CAC could significantly reduce the workload of radiologists. We propose an algorithm that both excludes negative scans and segments the CAC.

Authors

  • Leonardus B van den Oever
    University of Groningen, University Medical Center Groningen, Department of Radiation Oncology, Groningen, the Netherlands.
  • Ludo Cornelissen
    University of Groningen, University Medical Center Groningen, Department of Radiation Oncology, Groningen, the Netherlands.
  • Marleen Vonder
    Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
  • Congying Xia
    University of Groningen, University Medical Center Groningen, Department of Radiology, Groningen, the Netherlands.
  • Jurjen N van Bolhuis
    Lifelines Cohort Study, Groningen, the Netherlands.
  • Rozemarijn Vliegenthart
    University of Groningen, University Medical Center Groningen, Department of Radiology, Hanzeplein 1, 9713 GZ Groningen, The Netherlands.
  • Raymond N J Veldhuis
  • Geertruida H de Bock
    University of Groningen, University Medical Center Groningen, Department of Epidemiology, Hanzeplein 1, 9713 GZ Groningen, The Netherlands.
  • Matthijs Oudkerk
    University Medical Center, Groningen, The Netherlands.
  • 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.

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