Enhancing breast positioning quality through real-time AI feedback.

Journal: European radiology
Published Date: Jul 15, 2025

Abstract

OBJECTIVES: Enhance mammography quality to increase cancer detection by implementing continuous AI-driven feedback mechanisms, ensuring reliable, consistent, and high-quality screening by the 'Perfect', 'Good', 'Moderate', and 'Inadequate' (PGMI) criteria.

Authors

  • Raphael Sexauer
    Department of Radiology, University Hospital Basel, University of Basel, Basel, Switzerland. Electronic address: raphael.sexauer@usb.ch.
  • Friederike Riehle
    Department of Radiology and Nuclear Medicine, University Hospital Basel, Basel, Switzerland.
  • Karol Borkowski
    Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Switzerland. Electronic address: karol.borkowski@usz.ch.
  • Carlotta Ruppert
    Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Switzerland. Electronic address: Carlotta.ruppert@uzh.ch.
  • Silke Potthast
    Institute of Radiology, Limmatthal Hospital, Schlieren, Switzerland.
  • Noemi Schmidt
    Department of Radiology, University Hospital Basel, University of Basel, Switzerland. Electronic address: noemi.schmidt@usb.ch.

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