Free-water diffusion tensor imaging (fwDTI) was previously proposed to remove CSF partial volume effects of measures based on the diffusion tensor. Nevertheless, this diffusion-weighted technique is still subject to several pitfalls. In this study, an improved algorithm to fit the fwDTI to data acquired with two or more diffusion-weighting gradients is proposed. This algorithm is then used to explore the advantages and limitations of suppressing free-water in synthetic and in vivo diffusion-weighted data.
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