| |
|
|
|
|
|
|
|
|
1. |
Record Nr. |
UNINA9910254286103321 |
|
|
Titolo |
Modeling, Analysis, and Visualization of Anisotropy / / edited by Thomas Schultz, Evren Özarslan, Ingrid Hotz |
|
|
|
|
|
|
|
Pubbl/distr/stampa |
|
|
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
|
|
|
|
|
|
|
|
|
ISBN |
|
|
|
|
|
|
Edizione |
[1st ed. 2017.] |
|
|
|
|
|
Descrizione fisica |
|
1 online resource (X, 407 p. 150 illus. in color.) |
|
|
|
|
|
|
Collana |
|
Mathematics and Visualization, , 1612-3786 |
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
Soggetti |
|
Matrix theory |
Algebra |
Computer mathematics |
Mathematics |
Visualization |
Optical data processing |
Linear and Multilinear Algebras, Matrix Theory |
Computational Science and Engineering |
Image Processing and Computer Vision |
|
|
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
Nota di bibliografia |
|
Includes bibliographical references at the end of each chapters and index. |
|
|
|
|
|
|
|
|
Nota di contenuto |
|
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. |
|
|
|
|
|
|
|
|
Sommario/riassunto |
|
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. |
|
|
|
|
|
| |