AIR-MRF: Accelerated iterative reconstruction for magnetic resonance fingerprinting

Existing approaches for reconstruction of multiparametric maps with magnetic resonance fingerprinting (MRF) are currently limited by their estimation accuracy and reconstruction time. We aimed to address these issues with a novel combination of iterative reconstruction, fingerprint compression, addi...

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Bibliographic Details
Published in:Magnetic resonance imaging Vol. 41; pp. 29 - 40
Main Authors: Cline, Christopher C., Chen, Xiao, Mailhe, Boris, Wang, Qiu, Pfeuffer, Josef, Nittka, Mathias, Griswold, Mark A., Speier, Peter, Nadar, Mariappan S.
Format: Journal Article
Language:English
Published: Netherlands Elsevier Inc 01.09.2017
Subjects:
Accelerated
Algorithms
Brain - diagnostic imaging
Compression
Computer Simulation
Data Compression
Fast matching
Humans
Image Processing, Computer-Assisted - methods
Iterative
Magnetic Resonance Imaging - methods
MRF
Phantoms, Imaging
Radionuclide Imaging
Regularization
Reproducibility of Results
Software
MRF
Compression
Iterative
Accelerated
Regularization
Fast matching
ISSN:0730-725X, 1873-5894, 1873-5894
Online Access:Get full text
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Description
Summary:Existing approaches for reconstruction of multiparametric maps with magnetic resonance fingerprinting (MRF) are currently limited by their estimation accuracy and reconstruction time. We aimed to address these issues with a novel combination of iterative reconstruction, fingerprint compression, additional regularization, and accelerated dictionary search methods. The pipeline described here, accelerated iterative reconstruction for magnetic resonance fingerprinting (AIR-MRF), was evaluated with simulations as well as phantom and in vivo scans. We found that the AIR-MRF pipeline provided reduced parameter estimation errors compared to non-iterative and other iterative methods, particularly at shorter sequence lengths. Accelerated dictionary search methods incorporated into the iterative pipeline reduced the reconstruction time at little cost of quality.
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ISSN:0730-725X
1873-5894
1873-5894
DOI:10.1016/j.mri.2017.07.007