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Meeting Abstract

B0 field estimation using Ultrashort echo time/Dixon imaging with a 4-class tissue segmentation

MPS-Authors
/persons/resource/persons216104

Zhou,  J
Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons192852

Aghaeifar,  A
Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons83952

Hagberg,  G
Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons84187

Scheffler,  K
Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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https://www.ismrm.org/20/program_files/O66.htm
(Abstract)

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Citation

Zhou, J., Aghaeifar, A., Hagberg, G., & Scheffler, K. (2020). B0 field estimation using Ultrashort echo time/Dixon imaging with a 4-class tissue segmentation. In 2020 ISMRM & SMRT Virtual Conference & Exhibition (pp. 259-260).


Cite as: https://hdl.handle.net/21.11116/0000-0006-D7BB-5
Abstract
We use a UTE sequence combining with Dixon method to obtain the subject specific susceptibility distribution, with 4-class tissue segmentation. The susceptibility model was then used to simulate motion-induced B0 change for two head positions. A good agreement between the simulated and measured field map has been observe. A forward field map predicting strategy was explored using the susceptibility model.