Automated detection of lung cancer at ultralow dose PET/CT by deep neural networks - Initial results.

Journal: Lung cancer (Amsterdam, Netherlands)
Published Date: Nov 3, 2018

Abstract

OBJECTIVES: We evaluated whether machine learning may be helpful for the detection of lung cancer in FDG-PET imaging in the setting of ultralow dose PET scans.

Authors

  • Moritz Schwyzer
    Department of Nuclear Medicine, University Hospital Zurich, University of Zurich, Switzerland; Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Switzerland.
  • Daniela A Ferraro
    Department of Nuclear Medicine, University Hospital Zurich, University of Zurich, Switzerland.
  • Urs J Muehlematter
    Department of Nuclear Medicine, University Hospital Zurich, University of Zurich, Switzerland; Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Switzerland.
  • Alessandra Curioni-Fontecedro
    Department of Medical Oncology, University Hospital Zurich, University of Zurich, Switzerland.
  • Martin W Huellner
    Department of Nuclear Medicine, University Hospital Zurich, University of Zurich, Switzerland.
  • Gustav K von Schulthess
    Department of Nuclear Medicine, University Hospital Zurich, University of Zurich, Switzerland.
  • Philipp A Kaufmann
    Cardiac Imaging, Department of Nuclear Medicine, University Hospital Zurich, Zurich, Switzerland; and.
  • Irene A Burger
    Department of Nuclear Medicine, University Hospital Zurich, University of Zurich, Switzerland.
  • Michael Messerli
    Department of Nuclear Medicine, University Hospital Zurich, University of Zurich, Switzerland. Electronic address: michael.messerli@usz.ch.

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