Automating chest radiograph imaging quality control.

Journal: Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Published Date: Mar 23, 2021

Abstract

PURPOSE: To automate diagnostic chest radiograph imaging quality control (lung inclusion at all four edges, patient rotation, and correct inspiration) using convolutional neural network models.

Authors

  • Katri Nousiainen
    HUS Medical Imaging Center, Radiology, University of Helsinki and Helsinki University Hospital, P.O. Box 340, FI-00029 HUS, Helsinki, Finland; Department of Physics, University of Helsinki, P.O. Box 64, FI-00014 Helsinki, Finland.
  • Teemu Mäkelä
    HUS Medical Imaging Center, Radiology, University of Helsinki and Helsinki University Hospital, P.O. Box 340, FI-00029 HUS, Helsinki, Finland; Department of Physics, University of Helsinki, P.O. Box 64, FI-00014 Helsinki, Finland.
  • Anneli Piilonen
    HUS Medical Imaging Center, Radiology, University of Helsinki and Helsinki University Hospital, P.O. Box 340, FI-00029 HUS, Helsinki, Finland.
  • Juha I Peltonen
    HUS Medical Imaging Center, Radiology, University of Helsinki and Helsinki University Hospital, P.O. Box 340, FI-00029 HUS, Helsinki, Finland. Electronic address: juha.peltonen@hus.fi.

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