| Literature DB >> 28716682 |
Christopher C Cline1, Xiao Chen2, Boris Mailhe3, Qiu Wang3, Josef Pfeuffer4, Mathias Nittka4, Mark A Griswold5, Peter Speier4, Mariappan S Nadar3.
Abstract
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.Keywords: Accelerated; Compression; Fast matching; Iterative; MRF; Regularization
Mesh:
Year: 2017 PMID: 28716682 DOI: 10.1016/j.mri.2017.07.007
Source DB: PubMed Journal: Magn Reson Imaging ISSN: 0730-725X Impact factor: 2.546