In the course of development, the brain undergoes a remarkable process of restructuring as
it adapts to the environment and becomes more efficient in processing information. A variety …

Computational methods are crucial for the analysis of diffusion magnetic resonance imaging
(MRI) of the brain. Computational diffusion MRI can provide rich information at many size …

Finding the Riemannian center of mass or the Fréchet mean (FM) of manifold-valued data
sets is a commonly encountered problem in a variety of fields of Science and Engineering …

Statistical analysis of diffusion tensor imaging (DTI) data requires a computational
framework that is both numerically tractable (to account for the high dimensional nature of …

In this survey we review classical and recently proposed Riemannian metrics and
interpolation schemes on the space of symmetric positive definite (SPD) matrices. We …

A method for subject-specific assessment of neurological disorders, the method includes
receiving 3D image data representative of a subject's brain and identifying subject-specific …

The fiber orientation distribution function (FOD) is an advanced model for high angular
resolution diffusion MRI representing complex fiber geometry. However, the complicated …

Tractography refers to the process of tracing out the nerve fiber bundles from diffusion
Magnetic Resonance Images (dMRI) data acquired either in vivo or ex-vivo. Tractography is …

Cell selection algorithms are considered one of crucial features in LTE-Heterogeneous
Networks (HetNets). Due to different downlink transmit power levels and randomness …

Resolution is enhanced for diffusion MR imaging. The tensors modeling the underlying
water diffusion in brain tissues are used to interpolate other diffusion tensors, providing …