Multi-tissue constrained spherical deconvolution of diffusion MRI data yields white matter fibre orientation distributions, from which a quantitative metric of apparent fibre density can be obtained. Unlike most other diffusion MRI models, this fibre density metric is directly proportional to the diffusion-weighted signal magnitude, and thus intensity normalisation and bias field correction are needed to compare it between subjects in a study. Here we propose an intensity and inhomogeneity correction algorithm for multi-tissue constrained spherical deconvolution results, estimating a bias field and global normalisation in the log-domain. It outperforms a previously proposed approach that did not operate in the log-domain.
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