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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