Genetic algorithm search for the worst-case MRI RF exposure for a multiconfiguration implantable fixation system modeled using artificial neural networks.
RF-induced heating
artificial neural network
genetic algorithm
magnetic resonant imaging safety
specific absorption rate
Journal
Magnetic resonance in medicine
ISSN: 1522-2594
Titre abrégé: Magn Reson Med
Pays: United States
ID NLM: 8505245
Informations de publication
Date de publication:
11 2020
11 2020
Historique:
received:
02
01
2020
revised:
20
03
2020
accepted:
21
04
2020
pubmed:
28
5
2020
medline:
15
5
2021
entrez:
28
5
2020
Statut:
ppublish
Résumé
This paper presents a method to search for the worst-case configuration leading to the highest RF exposure for a multiconfiguration implantable fixation system under MRI. A two-step method combining an artificial neural network and a genetic algorithm is developed to achieve this purpose. In the first step, the level of RF exposure in terms of peak 1-g and/or 10-g averaged specific absorption rate (SAR The presented method can effectively identify the worst-case configuration and accurately predict the SAR The combination of an artificial neural network with genetic algorithm is a robust technique to determine the worst-case RF exposure level for a multiconfiguration system, and only needs a small amount of training data from the entire system.
Types de publication
Journal Article
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
2754-2764Informations de copyright
© 2020 International Society for Magnetic Resonance in Medicine.
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