Multi-tissue constrained spherical deconvolution (MT-CSD) exploits the characteristic b-value dependency of each tissue type to estimate both the apparent tissue densities and the full white matter (WM) fiber orientation distribution function from diffusion MRI data. In this work, we extend the MT-CSD approach to account for data acquired with nonlinear and multiple b-tensor shapes and show that multiple b-tensor shapes can provide a new means of contrast between tissue types, in particular between gray matter and WM. Our approach provides high-quality apparent tissue density maps and high-quality fiber tracking from data with multiple b-tensor shapes, even with sparse q-space samplings.
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