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research article

A Compressed Sensing Framework for Magnetic Resonance Fingerprinting

Davies, Mike
•
Puy, Gilles  
•
Vandergheynst, Pierre  
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2014
Siam Journal On Imaging Sciences

Inspired by the recently proposed Magnetic Resonance Fingerprinting (MRF) technique we develop a principled compressed sensing framework for quantitative MRI. The three key components are: a random pulse excitation sequence following the MRF technique; a random EPI subsampling strategy and an iterative projection algorithm that imposes consistency with the Bloch equations. We show that, as long as the excitation sequence possesses an appropriate form of persistent excitation, we are able to achieve accurate recovery the proton density, T1, T2 and off-resonance maps simultaneously from a limited number of samples.

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Type
research article
DOI
10.1137/130947246
ArXiv ID

1312.2465

Author(s)
Davies, Mike
Puy, Gilles  
Vandergheynst, Pierre  
Wiaux, Yves
Date Issued

2014

Publisher

Siam Publications

Published in
Siam Journal On Imaging Sciences
Volume

7

Issue

4

Start page

2623

End page

2656

Subjects

Compressed sensing

•

MRI

•

Bloch equations

•

manifolds

•

Johnston-Linderstrauss embedding

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LTS2  
Available on Infoscience
February 6, 2014
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/100419
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