First Performance Evaluation of an Artificial Intelligence-Based Computer-Aided Detection System for Pulmonary Nodule Evaluation in Dual-Source Photon-Counting Detector CT at Different Low-Dose Levels.

Journal: Investigative radiology
Published Date: Feb 1, 2022

Abstract

OBJECTIVE: The aim of this study was to evaluate the image quality (IQ) and performance of an artificial intelligence (AI)-based computer-aided detection (CAD) system in photon-counting detector computed tomography (PCD-CT) for pulmonary nodule evaluation at different low-dose levels.

Authors

  • Lisa Jungblut
    From the Institute of Diagnostic and Interventional Radiology.
  • Christian Blüthgen
    1 Institut für Diagnostische und Interventionelle Radiologie, Universitätsspital Zürich.
  • Malgorzata Polacin
    From the Institute of Diagnostic and Interventional Radiology.
  • Michael Messerli
    Department of Nuclear Medicine, University Hospital Zurich, University of Zurich, Switzerland. Electronic address: michael.messerli@usz.ch.
  • Bernhard Schmidt
    Siemens Healthineers, Forchheim, Germany.
  • André Euler
    Institute of Diagnostic and Interventional Radiology, University Hospital of Zurich, Zurich, Switzerland.
  • Hatem Alkadhi
  • Thomas Frauenfelder
  • Katharina Martini
    Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland.

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