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Abstract #0871

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

A new 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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