Loss Adaptive Dipole Inversion (LADI): A novel data driven approach for quantitative susceptibility mapping

This abstract presents a novel data driven approach for high quality QSM reconstructions without the use of complex and computationally intensive reconstruction models. The purpose of this approach is to develop a reconstruction technique which does not depend on the use of spatial priors from the magnitude image to remove artifacts and reduce blurring of edges. In our proposed formulation, the data fidelity term is updated based on the deviation of the estimated susceptibility map from the measured local field. With the proposed fidelity-loss adaptive reconstruction formulation, removal of artifacts was achieved without causing smoothing of sharp features.