Artificial Intelligence in Nuclear Medicine.


Journal

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
ISSN: 1535-5667
Titre abrégé: J Nucl Med
Pays: United States
ID NLM: 0217410

Informations de publication

Date de publication:
09 2019
Historique:
received: 01 04 2019
accepted: 16 05 2019
entrez: 5 9 2019
pubmed: 5 9 2019
medline: 13 6 2020
Statut: ppublish

Résumé

Despite the great media attention for artificial intelligence (AI), for many health care professionals the term and the functioning of AI remain a "black box," leading to exaggerated expectations on the one hand and unfounded fears on the other. In this review, we provide a conceptual classification and a brief summary of the technical fundamentals of AI. Possible applications are discussed on the basis of a typical work flow in medical imaging, grouped by planning, scanning, interpretation, and reporting. The main limitations of current AI techniques, such as issues with interpretability or the need for large amounts of annotated data, are briefly addressed. Finally, we highlight the possible impact of AI on the nuclear medicine profession, the associated challenges and, last but not least, the opportunities.

Identifiants

pubmed: 31481587
pii: jnumed.118.220590
doi: 10.2967/jnumed.118.220590
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

29S-37S

Informations de copyright

© 2019 by the Society of Nuclear Medicine and Molecular Imaging.

Auteurs

Felix Nensa (F)

Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany; and felix.nensa@uk-essen.de.

Aydin Demircioglu (A)

Department of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany; and.

Christoph Rischpler (C)

Department of Nuclear Medicine, University Hospital Essen, University of Duisburg-Essen, Germany.

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Classifications MeSH