Coil compression in simultaneous multislice functional MRI with concentric ring slice-GRAPPA and SENSE.
Magn Reson Med
; 76(4): 1196-209, 2016 10.
Article
em En
| MEDLINE
| ID: mdl-26507705
ABSTRACT
PURPOSE:
Simultaneous multislice (SMS) imaging is a useful way to accelerate functional magnetic resonance imaging (fMRI). As acceleration becomes more aggressive, an increasingly larger number of receive coils are required to separate the slices, which significantly increases the computational burden. We propose a coil compression method that works with concentric ring non-Cartesian SMS imaging and should work with Cartesian SMS as well. We evaluate the method on fMRI scans of several subjects and compare it to standard coil compression methods.METHODS:
The proposed method uses a slice-separation k-space kernel to simultaneously compress coil data into a set of virtual coils. Five subjects were scanned using both non-SMS fMRI and SMS fMRI with three simultaneous slices. The SMS fMRI scans were processed using the proposed method, along with other conventional methods. Code is available at https//github.com/alcu/sms.RESULTS:
The proposed method maintained functional activation with a fewer number of virtual coils than standard SMS coil compression methods. Compression of non-SMS fMRI maintained activation with a slightly lower number of virtual coils than the proposed method, but does not have the acceleration advantages of SMS fMRI.CONCLUSION:
The proposed method is a practical way to compress and reconstruct concentric ring SMS data and improves the preservation of functional activation over standard coil compression methods in fMRI. Magn Reson Med 761196-1209, 2016. © 2015 Wiley Periodicals, Inc.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Algoritmos
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Processamento de Sinais Assistido por Computador
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Encéfalo
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Mapeamento Encefálico
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Imageamento por Ressonância Magnética
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Interpretação de Imagem Assistida por Computador
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Compressão de Dados
Tipo de estudo:
Diagnostic_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2016
Tipo de documento:
Article