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

EXULT

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裁決

無聊的人

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

anachronistic

HARD

BIAS

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

thalamus

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