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In this paper, we introduce a statistical estimation framework for magnetic resonance fingerprinting (MRF), a recently proposed quantitative imaging paradigm. Within this framework, we present a maximum likelihood formulation to simultaneously estimate multiple parameter maps from highly undersampled, noisy k-space data. A novel iterative algorithm, based on variable splitting, the alternating direction...
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