Diffusion magnetic resonance imaging is a non-invasive technique to probe the microstructural features of tissue. Conventional diffusion encoding is unable to disentangle different microstructural features; therefore, multidimensional diffusion encoding has been proposed previously to solve this problem. Here we investigate different combinations of b-tensor encoding in a three-compartment model called SANDI. To estimate the size of soma in this model, we use frequency domain analysis because optimized b-tensor encoding waveforms do not provide a well-defined diffusion-time. The results show that different combinations of linear, planar, and spherical tensor encoding can improve the estimation of a specific parameter.
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