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Modeling, Analysis, and Visualization of Anisotropy

  • Thomas Schultz
  • Evren Özarslan
  • Ingrid Hotz

Part of the Mathematics and Visualization book series (MATHVISUAL)

Table of contents

  1. Front Matter
    Pages i-x
  2. Features and Visualization

    1. Front Matter
      Pages 1-1
    2. Bei Wang, Ingrid Hotz
      Pages 3-27
    3. Yue Zhang, Xiaofei Gao, Eugene Zhang
      Pages 29-41
    4. Roxana Bujack, Hans Hagen
      Pages 43-64
    5. Valentin Zobel, Markus Stommel, Gerik Scheuermann
      Pages 65-81
  3. Image Processing and Analysis

    1. Front Matter
      Pages 83-83
    2. Bernhard Burgeth, Andreas Kleefeld
      Pages 115-144
    3. Daniel Jörgens, Rodrigo Moreno
      Pages 145-173
  4. Diffusion Modeling and Microstructure

    1. Front Matter
      Pages 201-201
    2. Rutger H. J. Fick, Marco Pizzolato, Demian Wassermann, Rachid Deriche
      Pages 203-228
    3. Andrada Ianuş, Noam Shemesh, Daniel C. Alexander, Ivana Drobnjak
      Pages 229-255
    4. Bertil Wegmann, Anders Eklund, Mattias Villani
      Pages 257-282
    5. Snehlata Shakya, Nazre Batool, Evren Özarslan, Hans Knutsson
      Pages 283-308
  5. Tractography

    1. Front Matter
      Pages 309-309
    2. Zi’Ang Ding, Xavier Tricoche, Yaniv Gur
      Pages 311-330
    3. Xuan Gu, Anders Eklund, Hans Knutsson
      Pages 331-354
    4. L. Fonseca, C. van Pul, N. Lori, R. van den Boom, P. Andriessen, J. Buijs et al.
      Pages 355-372
  6. Machine Learning Approaches

    1. Front Matter
      Pages 373-373
    2. Mathew Monfort, Timothy Luciani, Jonathan Komperda, Brian Ziebart, Farzad Mashayek, G. Elisabeta Marai
      Pages 375-392
  7. Back Matter
    Pages 405-407

About these proceedings

Introduction

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.

Keywords

tensor tensor fields higher-order spherical harmonics visualization image processing medical imaging diffusion-weithed imaging (DWI) structural mechanics astrophysics statistics

Editors and affiliations

  • Thomas Schultz
    • 1
  • Evren Özarslan
    • 2
  • Ingrid Hotz
    • 3
  1. 1.Institute of Computer ScienceUniversity of BonnBonnGermany
  2. 2.Department of Biomedical Engineering (IMT)Linköping UniversityLinköpingSweden
  3. 3.Department of Science & TechnologyLinköping UniversityNorrköpingSweden

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-61358-1
  • Copyright Information Springer International Publishing AG 2017
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-319-61357-4
  • Online ISBN 978-3-319-61358-1
  • Series Print ISSN 1612-3786
  • Series Online ISSN 2197-666X
  • Buy this book on publisher's site
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