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Poster

MultiNet PyGRAPPA: A Novel Method for Highly Accelerated Metabolite Mapping

MPS-Authors
/persons/resource/persons192740

Nassirpour,  S
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Research Group MR Spectroscopy and Ultra-High Field Methodology, Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons192839

Chang,  P
Research Group MR Spectroscopy and Ultra-High Field Methodology, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons84402

Henning,  A
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Research Group MR Spectroscopy and Ultra-High Field Methodology, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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(Abstract)

https://www.ismrm.org/18/Electronic_Posters.pdf
(Abstract)

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Citation

Nassirpour, S., Chang, P., & Henning, A. (2018). MultiNet PyGRAPPA: A Novel Method for Highly Accelerated Metabolite Mapping. Poster presented at Joint Annual Meeting ISMRM-ESMRMB 2018, Paris, France.


Cite as: https://hdl.handle.net/21.11116/0000-0001-7DCA-0
Abstract
In this work, a novel acceleration method (MultiNet PyGrappa) is introduced which enables high in-plane acceleration factors for non-lipid suppressed 1H MRSI data. By using a variable density undersampling scheme and reconstructing the missing data points with multiple neural networks, this method enables a more robust reconstruction of highly undersampled data. High resolution metabolite maps acquired at 9.4T in the human brain using the proposed method are presented.