A Model-Based Approach to Accelerated Magnetic Resonance Fingerprinting Time Series Reconstruction
Bo Zhao1, Kawin Setsompop1, Borjan Gagoski2, Huihui Ye1, Elfar Adalsteinsson3, P. Ellen Grant2, and Larry L. Wald1
1Athinoula A. Martinos Center for Biomedical Imaging, Chalestown, MA, United States, 2Boston Children's Hospitial, Boston, MA, United States, 3EECS, MIT, Cambridge, MA, United States
model-based approach using low-rank and sparsity constraints is presented for
reconstructing the accelerated magnetic resonance fingerprinting (MRF)
time-series images. By enabling high-quality reconstructions of
contrast-weighted images from highly-undersampled data, the proposed method produces more accurate estimates
of tissue parameter maps compared to the conventional gridding based reconstruction
of the time-series. Ultimately, the goal is to reduce imaging time for MRF
acquisitions and improve spatial resolution.
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