Mathematics and Visualization

An Introduction to Tensors.- Feature Detection with Tensors.- Adaptive Structure Tensors and their Applications.- On the Concept of a Local Greyvalue Distribution and the Adaptive Estimation of a Structure Tensor.- Low-level Feature Detection Using the Boundary Tensor.- Diffusion Tensor Imaging.- An Introduction to Computational Diffusion MRI: the Diffusion Tensor and Beyond.- Random Noise in Diffusion Tensor Imaging, its Destructive Impact and Some Corrections.- An Introduction to Visualization of Diffusion Tensor Imaging and Its Applications.- Anatomy-Based Visualizations of Diffusion Tensor Images of Brain White Matter.- Variational Regularization of Multiple Diffusion Tensor Fields.- Higher Rank Tensors in Diffusion MRI.- Visualization of Tensor Fields.- Strategies for Direct Visualization of Second-Rank Tensor Fields.- Tensor Invariants and their Gradients.- Visualizing the Topology of Symmetric, Second-Order, Time-Varying Two-Dimensional Tensor Fields.- Degenerate 3D Tensors.- Locating Closed Hyperstreamlines in Second Order Tensor Fields.- Tensor Field Visualization Using a Metric Interpretation.- Tensor Field Transformations.- Symmetric Positive-Definite Matrices: From Geometry to Applications and Visualization.- Continuous Tensor Field Approximation of Diffusion Tensor MRI data.- Tensor Field Interpolation with PDEs.- Diffusion-Tensor Image Registration.- Image Processing Methods for Tensor Fields.- Tensor Median Filtering and M-Smoothing.- Mathematical Morphology on Tensor Data Using the Loewner Ordering.- A Local Structure Measure for Anisotropic Regularization of Tensor Fields.- Tensor Field Regularization using Normalized Convolution and Markov Random Fields in a Bayesian Framework.- PDEs for Tensor Image Processing.