A voxel-wise multivariate analysis based on the Mahalanobis distance is presented. Upon implementation on simulated DTI data, the method demonstrates the ability to detect regions of pathology at an individual level with respect to a reference healthy control group. This multivariate approach could enhance the clinical value of diffusion weighted MRI in the assessment of individual patients with highly spatially heterogeneous brain conditions such as traumatic brain injury or autism spectrum disorder.
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