European University Institute Library

Modeling, Analysis, and Visualization of Anisotropy, edited by Thomas Schultz, Evren Özarslan, Ingrid Hotz

Label
Modeling, Analysis, and Visualization of Anisotropy, edited by Thomas Schultz, Evren Özarslan, Ingrid Hotz
Language
eng
resource.imageBitDepth
0
Literary Form
non fiction
Main title
Modeling, Analysis, and Visualization of Anisotropy
Medium
electronic resource
Nature of contents
dictionaries
Oclc number
1021276842
Responsibility statement
edited by Thomas Schultz, Evren Özarslan, Ingrid Hotz
Series statement
Springer eBooksMathematics and Visualization,, 1612-3786
Summary
This book focuses on the modeling, processing and visualization of anisotropy, irrespective of the context in which it emerges, using state-of-the-art mathematical tools. As such, it differs substantially from conventional reference works, which are centered on a particular application. It covers the following topics: (i) the geometric structure of tensors, (ii) statistical methods for tensor field processing, (iii) challenges in mapping neural connectivity and structural mechanics, (iv) processing of uncertainty, and (v) visualizing higher-order representations. In addition to original research contributions, it provides insightful reviews. This multidisciplinary book is the sixth in a series that aims to foster scientific exchange between communities employing tensors and other higher-order representations of directionally dependent data. A significant number of the chapters were co-authored by the participants of the workshop titled Multidisciplinary Approaches to Multivalued Data: Modeling, Visualization, Analysis, which was held in Dagstuhl, Germany in April 2016. It offers a valuable resource for those working in the field of multi-directional data, vital inspirations for the development of new models, and essential analysis and visualization techniques, thus furthering the state-of-the-art in studies involving anisotropy.--, Provided by publisher
Table Of Contents
Part I: Features and Visualization -- Part II: Image Processing and Analysis -- Part III: Diffusion Modeling and Microstructure -- Part IV: Tractography -- Part V: Machine Learning Approaches
Content
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