Visualization and Processing of Tensor Fields
Başlık
Visualization and Processing of Tensor Fields

ISBNp
9783540312727

Dil
English

Standart Tanımlama
10.1007/3-540-31272-2

Yayın Bilgileri
Berlin, Heidelberg : Springer Berlin Heidelberg, 2006.

Fiziksel Tanımlama
XV, 481 p. online resource.

Seri
Mathematics and Visualization,

İçerik
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.

Özet
Matrix-valued data sets - so-called second order tensor fields - have gained significant importance in scientific visualization and image processing due to recent developments such as diffusion tensor imaging. This book is the first edited volume that presents the state-of-the-art in the visualization and processing of tensor fields. It contains some longer chapters dedicated to surveys and tutorials of specific topics, as well as a great deal of original work by leading experts that has not been published before. It serves as an overview for the inquiring scientist, as a basic foundation for developers and practitioners, and as as a textbook for specialized classes and seminars for graduate and doctoral students.

Konu Başlığı
Mathematics.
 
Radiology.
 
Computer graphics.
 
Image processing.
 
Mathematical analysis.
 
Analysis (Mathematics).
 
Visualization.
 
Differential geometry.
 
Analysis.
 
Imaging / Radiology.
 
Computer Imaging, Vision, Pattern Recognition and Graphics.
 
Image Processing and Computer Vision.

Ek Yazar
Weickert, Joachim.
 
Hagen, Hans.

Ek Kurum Yazarı
SpringerLink (Online service)

Elektronik Erişim
http://dx.doi.org/10.1007/3-540-31272-2


Materyal TürüDemirbaş NumarasıYer NumarasıRaf KonumuMevcut Konumu
E-Kitap1818840-1001QA299.6 -433SPRINGER E-Kitap KoleksiyonuSpringer E-Kitap Koleksiyonu