In this work noise is assumed to be a random vector and the method of unbiased predictive risk estimator (UPRE) is used to select suitable data/regularization parameters to solve the local phase to susceptibility deconvolution problem of quantitative susceptibility mapping (QSM). The proposed algorithm is tested on the simulated multi-echo data provided at the 2019 QSM Reconstruction Challenge. This work is a further development of the algorithm presented at the ISMRM Meeting 2021 and its purpose is to show that the method of UPRE can be applied advantageously to a shearlet /TGV based susceptibility reconstruction.
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