The diffusion MRI signal, as measured with conventional linear tensor encoding (LTE), has been shown to have not enough features to fully model the white matter microstructure. Here we investigate whether adding spherical encoding (STE) to LTE makes microstructural parameter estimation more robust. On signal simulations and in in vivo MRI data, we demonstrate that the intra-axonal diffusivity and axonal water fraction are estimated with higher precision, thereby enabling a 20 minute whole brain protocol to extract brain microstructural parameters without imposing constraints or priors.
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