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Multiscale reconstruction for MR fingerprinting
Author(s) -
Pierre Eric Y.,
Ma Dan,
Chen Yong,
Badve Chaitra,
Griswold Mark A.
Publication year - 2016
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.25776
Subject(s) - computer science , artificial intelligence , iterative reconstruction , image resolution , parametric statistics , pattern recognition (psychology) , pixel , algorithm , convergence (economics) , matching (statistics) , imaging phantom , computer vision , mathematics , physics , statistics , economics , optics , economic growth
Purpose To reduce the acquisition time needed to obtain reliable parametric maps with Magnetic Resonance Fingerprinting. Methods An iterative‐denoising algorithm is initialized by reconstructing the MRF image series at low image resolution. For subsequent iterations, the method enforces pixel‐wise fidelity to the best‐matching dictionary template then enforces fidelity to the acquired data at slightly higher spatial resolution. After convergence, parametric maps with desirable spatial resolution are obtained through template matching of the final image series. The proposed method was evaluated on phantom and in vivo data using the highly undersampled, variable‐density spiral trajectory and compared with the original MRF method. The benefits of additional sparsity constraints were also evaluated. When available, gold standard parameter maps were used to quantify the performance of each method. Results The proposed approach allowed convergence to accurate parametric maps with as few as 300 time points of acquisition, as compared to 1000 in the original MRF work. Simultaneous quantification of T1, T2, proton density (PD), and B 0 field variations in the brain was achieved in vivo for a 256 × 256 matrix for a total acquisition time of 10.2 s, representing a three‐fold reduction in acquisition time. Conclusion The proposed iterative multiscale reconstruction reliably increases MRF acquisition speed and accuracy. Magn Reson Med 75:2481–2492, 2016. © 2015 Wiley Periodicals, Inc.