Unknown

Dataset Information

0

Improved magnetic resonance fingerprinting reconstruction with low-rank and subspace modeling.


ABSTRACT: PURPOSE:This article introduces a constrained imaging method based on low-rank and subspace modeling to improve the accuracy and speed of MR fingerprinting (MRF). THEORY AND METHODS:A new model-based imaging method is developed for MRF to reconstruct high-quality time-series images and accurate tissue parameter maps (e.g., T1 , T2 , and spin density maps). Specifically, the proposed method exploits low-rank approximations of MRF time-series images, and further enforces temporal subspace constraints to capture magnetization dynamics. This allows the time-series image reconstruction problem to be formulated as a simple linear least-squares problem, which enables efficient computation. After image reconstruction, tissue parameter maps are estimated via dictionary-based pattern matching, as in the conventional approach. RESULTS:The effectiveness of the proposed method was evaluated with in vivo experiments. Compared with the conventional MRF reconstruction, the proposed method reconstructs time-series images with significantly reduced aliasing artifacts and noise contamination. Although the conventional approach exhibits some robustness to these corruptions, the improved time-series image reconstruction in turn provides more accurate tissue parameter maps. The improvement is pronounced especially when the acquisition time becomes short. CONCLUSIONS:The proposed method significantly improves the accuracy of MRF, and also reduces data acquisition time. Magn Reson Med 79:933-942, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

SUBMITTER: Zhao B 

PROVIDER: S-EPMC5641478 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

altmetric image

Publications

Improved magnetic resonance fingerprinting reconstruction with low-rank and subspace modeling.

Zhao Bo B   Setsompop Kawin K   Adalsteinsson Elfar E   Gagoski Borjan B   Ye Huihui H   Ma Dan D   Jiang Yun Y   Ellen Grant P P   Griswold Mark A MA   Wald Lawrence L LL  

Magnetic resonance in medicine 20170415 2


<h4>Purpose</h4>This article introduces a constrained imaging method based on low-rank and subspace modeling to improve the accuracy and speed of MR fingerprinting (MRF).<h4>Theory and methods</h4>A new model-based imaging method is developed for MRF to reconstruct high-quality time-series images and accurate tissue parameter maps (e.g., T<sub>1</sub> , T<sub>2</sub> , and spin density maps). Specifically, the proposed method exploits low-rank approximations of MRF time-series images, and furthe  ...[more]

Similar Datasets

| S-EPMC7755311 | biostudies-literature
| S-EPMC5585028 | biostudies-literature
| S-EPMC9825911 | biostudies-literature
| S-EPMC7611820 | biostudies-literature
| S-EPMC3602925 | biostudies-literature
| S-EPMC9339522 | biostudies-literature
| S-EPMC3602020 | biostudies-literature
| S-EPMC5123982 | biostudies-literature
| S-EPMC7083689 | biostudies-literature
| S-EPMC6519164 | biostudies-literature