The estimation of reliable parameters of multi-compartment models of water diffusivity is a challenging open problem, especially when low-SNR clinical-datasets are analyzed. The ill-posedness of the models requires fixing a subset of parameters in order to estimate the rest of them. We propose a simple and fast method where only averaged parameters are required (not voxelwise information is required). The method is based on the processing of powder-averaged data to estimate a robust value for the axon-bundle parallel-diffusivity. We test the robustness of the method on synthetic experiments and show the results on in-vivo human and ex-vivo rodent datasets.
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