Pneumonia Detection in Chest X-Ray Dose-Equivalent CT: Impact of Dose Reduction on Detectability by Artificial Intelligence.

Journal: Academic radiology
Published Date: Jul 1, 2020

Abstract

RATIONALE AND OBJECTIVES: There has been a significant increase of immunocompromised patients in recent years due to new treatment modalities for previously fatal diseases. This comes at the cost of an elevated risk for infectious diseases, most notably pathogens affecting the respiratory tract. Because early diagnosis and treatment of pneumonia can help reducing morbidity and mortality, we assessed the performance of a deep neural network in the detection of pulmonary infection in chest X-ray dose-equivalent computed tomography (CT).

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.
  • Katharina Martini
    Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland.
  • Stephan Skawran
    Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Rämistrasse 100, CH-8091 Zurich, Switzerland; University of Zurich, Zurich, Switzerland.
  • Michael Messerli
    Department of Nuclear Medicine, University Hospital Zurich, University of Zurich, Switzerland. Electronic address: michael.messerli@usz.ch.
  • Thomas Frauenfelder

Keywords

External Resources

Popular Topics
Recent Journals