Parallel imaging for reduction of scanning time is now routinely used in clinical practice. The spatial information from the coils’ profiles are exploited for encoding. The nonlinear inversion reconstruction is a calibrationless parallel imaging technique, which jointly estimate coil sensitivities and image content. In this work, we demonstrate how to combine such a calibrationless parallel imaging technique with an advanced neural network based image prior for efficient MR imaging.
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