| Dewey Class |
512.5 |
| Title |
Modeling, Analysis, and Visualization of Anisotropy ([EBook]) / edited by Thomas Schultz, Evren ?arslan, Ingrid Hotz. |
| Added Personal Name |
Schultz, Thomas editor. |
| ?arslan, Evren editor. |
| Hotz, Ingrid editor. |
| Other name(s) |
SpringerLink (Online service) |
| Publication |
Cham : Springer International Publishing : Imprint: Springer , 2017. |
| Physical Details |
X, 407 p. 150 illus. in color : online resource. |
| Series |
Mathematics and Visualization 1612-3786 |
| ISBN |
9783319613581 |
| Summary Note |
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.: |
| Contents note |
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. |
| System details note |
Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users) |
| Internet Site |
http://dx.doi.org/10.1007/978-3-319-61358-1 |
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