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Abstract

System(s) and method(s) are provided to enable imaging-based identification, detection, evaluation, and mapping of white matter microstructure and hemispheric organization of white matter in a central nervous system (CNS) structure afflicted by a neurological disease or disorder. Various embodiments exploit a set of diffusion tensor metrics to define a classification sub-space and determine a multivariate classifier through training data related to at least two groups of subjects: a first group of subjects afflicted by the neurological disease or neurological disorder, and a second group of subjects typically developing. The set of diffusion tensor metrics can be selected based at least on clinical information related to the neurological disease or neurological disorder and anatomy of CNS structure. Inclusion of tensor skewness asymmetry in such set yields an increase in sensitivity, specificity, accuracy, reliability, and predictive ability of the biological discrimination of subjects with and without a neurological disease or neurological disorder.

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