Nuclear medicine technologists practice impacted by AI denoising applications in PET/CT images.

Journal: Radiography (London, England : 1995)
PMID: 38917681

Abstract

PURPOSE: Artificial intelligence (AI) in positron emission tomography/computed tomography (PET/CT) can be used to improve image quality when it is useful to reduce the injected activity or the acquisition time. Particular attention must be paid to ensure that users adopt this technological innovation when outcomes can be improved by its use. The aim of this study was to identify the aspects that need to be analysed and discussed to implement an AI denoising PET/CT algorithm in clinical practice, based on the representations of Nuclear Medicine Technologists (NMT) from Western-Switzerland, highlighting the barriers and facilitators associated.

Authors

  • M Champendal
    School of Health Sciences HESAV, HES-SO, University of Applied Sciences Western Switzerland: Lausanne, CH, Switzerland; Faculty of Biology and Medicine, University of Lausanne, Lausanne, CH, Switzerland. Electronic address: melanie.champendal@hesav.ch.
  • R S T Ribeiro
    School of Health Sciences HESAV, HES-SO, University of Applied Sciences Western Switzerland: Lausanne, CH, Switzerland. Electronic address: ricardo.ribeiro@hesav.ch.
  • H Müller
    Informatics Institute, University of Applied Sciences Western Switzerland (HES-SO Valais) Sierre, CH, Switzerland; Medical Faculty, University of Geneva, CH, Switzerland. Electronic address: henning.mueller@hevs.ch.
  • J O Prior
    Faculty of Biology and Medicine, University of Lausanne, Lausanne, CH, Switzerland; Nuclear Medicine and Molecular Imaging Department, Lausanne University Hospital (CHUV): Lausanne, CH, Switzerland. Electronic address: john.prior@unil.ch.
  • C Sá Dos Reis
    School of Health Sciences HESAV, HES-SO, University of Applied Sciences Western Switzerland: Lausanne, CH, Switzerland. Electronic address: claudia.sadosreis@hesav.ch.

Keywords

External Resources

Popular Topics
Recent Journals