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.

Abstract: A method for estimating a value of a diffusion tensor includes obtaining, from a plurality of test subjects, DT-MRI data from which an initial estimate of the tensor can be derived. Values indicative of intra-subject variation and inter-subject variation in the data are then determined. These values are used to determine a subject-specific additive offset for adjusting the DT-MRI data.

Abstract: A method for estimating a value of a diffusion tensor includes obtaining, from a plurality of test subjects, DT-MRI data from which an initial estimate of the tensor can be derived. Values indicative of int-subject variation and inter-subject variation in the data are then determined. These values are used to determine a subject-specific additive offset for adjusting the DT-MRI data.