In MR-STAT, data from a sequence of time-varying RF pulses and gradient encodings is reconstructed into multiple quantitative parameter maps by solving a large scale inversion problem. The combined interaction of RF and gradient events determines the noise-propagation into the reconstructed maps. We derive a computationally efficient performance metric to study this effect, by analyzing the block-diagonal of the k-space representation of the Jacobian. This allows for extremely fast prediction of the noise spectrum of the reconstructed parameter maps.
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