An advanced signal model-based reconstruction jointly estimating image and field map from multi-echo, multi-coil acquisition of hyperpolarized metabolic data was developed and validated using synthetic and in-vivo data. Relative to standard multi-echo reconstruction methods, reconstruction accuracy improved by up to 30% for synthetic data considering realistic noise levels and field map gradients. Geometric distortion correction resulted in less than 20% error. For in-vivo data, the average improvement was 15%. Depending on the direction of the field gradients present, multi-coil reconstruction was found to be beneficial for addressing signal folding issues.
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