The analysis of the whole-brain statistical variability maps corresponding to different statistical coefficients provides quantitative and anatomical information regarding the reproducibility, reliability or biological variability of diffusion MRI data. However, the separate analysis of each statistical map cannot reveal the emerging relationships that exist between these three properties of the data and their interactions across the brain anatomy. In this abstract, we present a new integrated multi-parametric segmentation approach for the combined visualisation and analysis of the reproducibility, reliability and biological variability maps using diffusion MRI data acquired from an older population.
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