Titlebook: Visualization and Processing of Higher Order Descriptors for Multi-Valued Data; Ingrid Hotz,Thomas Schultz Conference proceedings 2015 Spr

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Visualization of Diffusion Propagator and Multiple Parameter Diffusion Signal multiple b-values, multiple orientations and multiple diffusion times. These new and demanding acquisitions go beyond classical diffusion tensor imaging (DTI) and single b-value high angular resolution diffusion imaging (HARDI) acquisitions. Recent studies show that such multiple parameter diffusio

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Visualizing Symmetric Indefinite 2D Tensor Fields Using the Heat Kernel Signaturee, and multiscale nature, it has been successfully applied in many geometric applications. From a more general point of view, the HKS can be considered as a descriptor of the metric of a Riemannian manifold. Given a symmetric positive definite tensor field we may interpret it as the metric of some R

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A Framework for the Analysis of Diffusion Compartment Imaging (DCI)e gained in vivo by means of diffusion-weighted imaging that is sensitive to the local patterns of diffusion of water molecules throughout the brain. Diffusion compartment imaging (DCI) provides a separate parameterization for the diffusion signal arising from each compartment of water molecules at

CUMB

Statistical and Machine Learning Methods for Neuroimaging: Examples, Challenges, and Extensions to Dn. In this chapter, we survey two broad families of approaches to quantitative analysis of neuroimaging data: statistical testing and machine learning. We discuss how methods developed for traditional scalar structural neuroimaging data have been extended to diffusion magnetic resonance imaging data