State of the Art in Lung Ultrasound, Shifting from Qualitative to Quantitative Analyses.
Artificial intelligence
Image processing
In vitro
In vivo
Lung ultrasound
Quantitative lung ultrasound
Review
Signal processing
Journal
Ultrasound in medicine & biology
ISSN: 1879-291X
Titre abrégé: Ultrasound Med Biol
Pays: England
ID NLM: 0410553
Informations de publication
Date de publication:
12 2022
12 2022
Historique:
received:
12
05
2022
revised:
12
07
2022
accepted:
15
07
2022
pubmed:
27
9
2022
medline:
28
10
2022
entrez:
26
9
2022
Statut:
ppublish
Résumé
Lung ultrasound (LUS) has been increasingly expanding since the 1990s, when the clinical relevance of vertical artifacts was first reported. However, the massive spread of LUS is only recent and is associated with the coronavirus disease 2019 (COVID-19) pandemic, during which semi-quantitative computer-aided techniques were proposed to automatically classify LUS data. In this review, we discuss the state of the art in LUS, from semi-quantitative image analysis approaches to quantitative techniques involving the analysis of radiofrequency data. We also discuss recent in vitro and in silico studies, as well as research on LUS safety. Finally, conclusions are drawn highlighting the potential future of LUS.
Identifiants
pubmed: 36155147
pii: S0301-5629(22)00482-3
doi: 10.1016/j.ultrasmedbio.2022.07.007
pmc: PMC9499741
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
2398-2416Informations de copyright
Copyright © 2022 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of Competing Interest All authors declare no conflicts of interest.
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