Automated detection of pulmonary embolism from CT-angiograms using deep learning.

Journal: BMC medical imaging
Published Date: Mar 14, 2022

Abstract

BACKGROUND: The aim of this study was to develop and evaluate a deep neural network model in the automated detection of pulmonary embolism (PE) from computed tomography pulmonary angiograms (CTPAs) using only weakly labelled training data.

Authors

  • Heidi Huhtanen
    Department of Radiology, University of Turku and Turku University Hospital, Turku, Finland. hejohuh@utu.fi.
  • Mikko Nyman
    Department of Radiology, University of Turku and Turku University Hospital, Turku, Finland.
  • Tarek Mohsen
    Reaktor Innovations Oy, Helsinki, Finland.
  • Arho Virkki
    Auria Clinical Informatics, Turku University Hospital, Turku, Finland.
  • Antti Karlsson
    Department of Radiology, University of Turku, Turku, Finland, and Pihlajalinna Turku, Turku, Finland.
  • Jussi Hirvonen
    Department of Radiology, Turku University Hospital & University of Turku, Kiinamyllynkatu 4-8, 20521 Turku, Finland.

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