Suppressing Multi-Channel Ultra-Low-Field MRI Measurement Noise Using Data Consistency and Image Sparsity

Ultra-low-field (ULF) MRI (B (0) = 10–100 µT) typically suffers from a low signal-to-noise ratio (SNR). While SNR can be improved by pre-polarization and signal detection using highly sensitive superconducting quantum interference device (SQUID) sensors, we propose to use the inter-dependency of the...

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Autores principales: Lin, Fa-Hsuan, Vesanen, Panu T., Hsu, Yi-Cheng, Nieminen, Jaakko O., Zevenhoven, Koos C. J., Dabek, Juhani, Parkkonen, Lauri T., Simola, Juha, Ahonen, Antti I., Ilmoniemi, Risto J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3633989/
https://www.ncbi.nlm.nih.gov/pubmed/23626710
http://dx.doi.org/10.1371/journal.pone.0061652
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author Lin, Fa-Hsuan
Vesanen, Panu T.
Hsu, Yi-Cheng
Nieminen, Jaakko O.
Zevenhoven, Koos C. J.
Dabek, Juhani
Parkkonen, Lauri T.
Simola, Juha
Ahonen, Antti I.
Ilmoniemi, Risto J.
author_facet Lin, Fa-Hsuan
Vesanen, Panu T.
Hsu, Yi-Cheng
Nieminen, Jaakko O.
Zevenhoven, Koos C. J.
Dabek, Juhani
Parkkonen, Lauri T.
Simola, Juha
Ahonen, Antti I.
Ilmoniemi, Risto J.
author_sort Lin, Fa-Hsuan
collection PubMed
description Ultra-low-field (ULF) MRI (B (0) = 10–100 µT) typically suffers from a low signal-to-noise ratio (SNR). While SNR can be improved by pre-polarization and signal detection using highly sensitive superconducting quantum interference device (SQUID) sensors, we propose to use the inter-dependency of the k-space data from highly parallel detection with up to tens of sensors readily available in the ULF MRI in order to suppress the noise. Furthermore, the prior information that an image can be sparsely represented can be integrated with this data consistency constraint to further improve the SNR. Simulations and experimental data using 47 SQUID sensors demonstrate the effectiveness of this data consistency constraint and sparsity prior in ULF-MRI reconstruction.
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spelling pubmed-36339892013-04-26 Suppressing Multi-Channel Ultra-Low-Field MRI Measurement Noise Using Data Consistency and Image Sparsity Lin, Fa-Hsuan Vesanen, Panu T. Hsu, Yi-Cheng Nieminen, Jaakko O. Zevenhoven, Koos C. J. Dabek, Juhani Parkkonen, Lauri T. Simola, Juha Ahonen, Antti I. Ilmoniemi, Risto J. PLoS One Research Article Ultra-low-field (ULF) MRI (B (0) = 10–100 µT) typically suffers from a low signal-to-noise ratio (SNR). While SNR can be improved by pre-polarization and signal detection using highly sensitive superconducting quantum interference device (SQUID) sensors, we propose to use the inter-dependency of the k-space data from highly parallel detection with up to tens of sensors readily available in the ULF MRI in order to suppress the noise. Furthermore, the prior information that an image can be sparsely represented can be integrated with this data consistency constraint to further improve the SNR. Simulations and experimental data using 47 SQUID sensors demonstrate the effectiveness of this data consistency constraint and sparsity prior in ULF-MRI reconstruction. Public Library of Science 2013-04-23 /pmc/articles/PMC3633989/ /pubmed/23626710 http://dx.doi.org/10.1371/journal.pone.0061652 Text en © 2013 Lin et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Lin, Fa-Hsuan
Vesanen, Panu T.
Hsu, Yi-Cheng
Nieminen, Jaakko O.
Zevenhoven, Koos C. J.
Dabek, Juhani
Parkkonen, Lauri T.
Simola, Juha
Ahonen, Antti I.
Ilmoniemi, Risto J.
Suppressing Multi-Channel Ultra-Low-Field MRI Measurement Noise Using Data Consistency and Image Sparsity
title Suppressing Multi-Channel Ultra-Low-Field MRI Measurement Noise Using Data Consistency and Image Sparsity
title_full Suppressing Multi-Channel Ultra-Low-Field MRI Measurement Noise Using Data Consistency and Image Sparsity
title_fullStr Suppressing Multi-Channel Ultra-Low-Field MRI Measurement Noise Using Data Consistency and Image Sparsity
title_full_unstemmed Suppressing Multi-Channel Ultra-Low-Field MRI Measurement Noise Using Data Consistency and Image Sparsity
title_short Suppressing Multi-Channel Ultra-Low-Field MRI Measurement Noise Using Data Consistency and Image Sparsity
title_sort suppressing multi-channel ultra-low-field mri measurement noise using data consistency and image sparsity
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3633989/
https://www.ncbi.nlm.nih.gov/pubmed/23626710
http://dx.doi.org/10.1371/journal.pone.0061652
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