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 MultivaluedData: 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.

Includes works performed in very different areas as long as they are consistent with the central theme of the book Will help to enable transfer of knowledge between different disciplines potentially leading to significant advances Will bridge the gap between application-oriented and theoretical studies Great resources for junior scientists and those who would like to have an up-to-date information on the ongoing developments

Inhalt
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.