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A hybrid FDTD/MoM algorithm with a conformal Huygens' equivalent surface for MRI RF coil design and analysis.
Liu, Yang; Wang, Qiuliang; Liu, Feng.
Afiliação
  • Liu Y; Key Laboratory of Applied Superconductivity, Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing 100190, China; School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China.
  • Wang Q; Key Laboratory of Applied Superconductivity, Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing 100190, China; School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China. Electronic address: qiuliang@mail.iee.ac.cn.
  • Liu F; School of Information Technology and Electrical Engineering, The University of Queensland, St. Lucia, Brisbane, Qld 4072, Australia.
Magn Reson Imaging ; 102: 1-8, 2023 10.
Article em En | MEDLINE | ID: mdl-36963640
ABSTRACT
Accurate design and analysis of radiofrequency (RF) coils are crucial for ultra-high field (UHF) magnetic resonance imaging (MRI) applications. To improve the numerical accuracy of electromagnetic (EM) simulations, we propose a hybrid finite difference time domain (FDTD)/method of moments (MoM) method. Unlike conventional cuboid-like Huygens' equivalent surfaces (HES), we proposed to use a conformal HES to interface the EM data of the FDTD and MoM zone. The shape and size of the conformal surface can be adjusted to fit different RF coil models, thus broadening the application range of the hybrid FDTD/MoM method. Two numerical models an 8-channel ellipse array, and an 8-channel bent dipole array, are simulated and compared with the conventional HES counterpart. Numerical results demonstrate the capability of the conformal HES method in the analysis of RF coils.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Algoritmos / Imageamento por Ressonância Magnética Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Algoritmos / Imageamento por Ressonância Magnética Idioma: En Ano de publicação: 2023 Tipo de documento: Article