Simultaneous proton (1H) and sodium (23Na) acquisition can provide important metabolic information. However, proton data may suffer from off-resonance artifacts due to the long dwell time required to obtain sufficient SNR for 23Na. In this work we use center outward and center inward image pairs to train a convolutional neural network that performs an off-resonance correction for the proton data without an additional measured field map.
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