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Scientific Visualization

Uncertainty, Multifield, Biomedical, and Scalable Visualization

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  • © 2014

Overview

Editors:
  1. Charles D. Hansen

    1. School of Computing Scientific Computing and Imaging Institu, University of Utah, Salt Lake City, USA

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  2. Min Chen

    1. e-Research Centre, University of Oxford, Oxford, United Kingdom

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  3. Christopher R. Johnson

    1. School of Computing Scientific Computing and Imaging Institu, University of Utah, Salt Lake City, USA

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  4. Arie E. Kaufman

    1. Department of Computer Science, Stony Brook University, New York, USA

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  5. Hans Hagen

    1. Fachbereich Informatik, Technische Universität Kaiserslautern, Kaiserslautern, Germany

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  • Provides an introduction to uncertainty visualization, multi field visualization, biomedical visualization and scalable visualization
  • Provides in-depth examples of each of these topics and the mathematical process for implementing the examples
  • Provides applications of each of these topics to real world problems
  • Includes supplementary material: sn.pub/extras

Part of the book series: Mathematics and Visualization (MATHVISUAL)

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Table of contents (31 chapters)

  1. Front Matter

    Pages i-xvii
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  2. Uncertainty Visualization

    1. Front Matter

      Pages 1-1
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    2. Overview and State-of-the-Art of Uncertainty Visualization

      • Georges-Pierre Bonneau, Hans-Christian Hege, Chris R. Johnson, Manuel M. Oliveira, Kristin Potter, Penny Rheingans et al.
      Pages 3-27

    3. Uncertainty Visualization and Color Vision Deficiency

      • Manuel M. Oliveira
      Pages 29-33

    4. Analysis of Uncertain Scalar Data with Hixels

      • Joshua A. Levine, David Thompson, Janine C. Bennett, Peer-Timo Bremer, Attila Gyulassy, Valerio Pascucci et al.
      Pages 35-44

    5. On the (Un)Suitability of Strict Feature Definitions for Uncertain Data

      • Tino Weinkauf
      Pages 45-50

    6. The Haunted Swamps of Heuristics: Uncertainty in Problem Solving

      • Artem Amirkhanov, Stefan Bruckner, Christoph Heinzl, M. Eduard Gröller
      Pages 51-60

    7. Visualizing Uncertainty in Predictive Models

      • Penny Rheingans, Marie desJardins, Wallace Brown, Alex Morrow, Doug Stull, Kevin Winner
      Pages 61-69

    8. Incorporating Uncertainty in Intrusion Detection to Enhance Decision Making

      • Lane Harrison, Aidong Lu
      Pages 71-78

    9. Fuzzy Fibers: Uncertainty in dMRI Tractography

      • Thomas Schultz, Anna Vilanova, Ralph Brecheisen, Gordon Kindlmann
      Pages 79-92

    10. Mathematical Foundations of Uncertain Field Visualization

      • Gerik Scheuermann, Mario Hlawitschka, Christoph Garth, Hans Hagen
      Pages 93-101

  3. Multifield Visualization

    1. Front Matter

      Pages 103-104
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    2. Definition of a Multifield

      • Ingrid Hotz, Ronald Peikert
      Pages 105-109

    3. Categorization

      • Helwig Hauser, Hamish Carr
      Pages 111-117

    4. Fusion of Visual Channels

      • Min Chen, Klaus Mueller, Anders Ynnerman
      Pages 119-127

    5. Glyph-Based Multi-field Visualization

      • David H.S. Chung, Robert S. Laramee, Johannes Kehrer, Helwig Hauser
      Pages 129-137

    6. Derived Fields

      • Eugene Zhang, Vijay Natarajan
      Pages 139-159

    7. Interactive Visual Exploration and Analysis

      • Gunther H. Weber, Helwig Hauser
      Pages 161-173

    8. Visual Exploration of Multivariate Volume Data Based on Clustering

      • Lars Linsen
      Pages 175-187

    9. Feature-Based Visualization of Multifields

      • Harald Obermaier, Ronald Peikert
      Pages 189-196
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Keywords

About this book

Based on the seminar that took place in Dagstuhl, Germany in June 2011, this contributed volume studies the four important topics within the scientific visualization field: uncertainty visualization, multifield visualization, biomedical visualization and scalable visualization.

• Uncertainty visualization deals with uncertain data from simulations or sampled data, uncertainty due to the mathematical processes operating on the data, and uncertainty in the visual representation,
• Multifield visualization addresses the need to depict multiple data at individual locations and the combination of multiple datasets,
• Biomedical is a vast field with select subtopics addressed from scanning methodologies to structural applications to biological applications,
• Scalability in scientific visualization is critical as data grows and computational devices range from hand-held mobile devices to exascale computational platforms.

Scientific Visualization will be useful to practitioners of scientific visualization, students interested in both overview and advanced topics, and those interested in knowing more about the visualization process.

Reviews

From the book reviews:

“This carefully edited volume consists of papers contributed by the participants of a seminar held in Dagstuhl, Germany in 2011. … The book will surely be well received by scientists, engineers, and medical practitioners. It is a must-have for a scientific library.” (Soubhik Chakraborty, Computing Reviews, February, 2015)

Editors and Affiliations

  • School of Computing Scientific Computing and Imaging Institu, University of Utah, Salt Lake City, USA

    Charles D. Hansen, Christopher R. Johnson

  • e-Research Centre, University of Oxford, Oxford, United Kingdom

    Min Chen

  • Department of Computer Science, Stony Brook University, New York, USA

    Arie E. Kaufman

  • Fachbereich Informatik, Technische Universität Kaiserslautern, Kaiserslautern, Germany

    Hans Hagen

Bibliographic Information

  • Book Title: Scientific Visualization

  • Book Subtitle: Uncertainty, Multifield, Biomedical, and Scalable Visualization

  • Editors: Charles D. Hansen, Min Chen, Christopher R. Johnson, Arie E. Kaufman, Hans Hagen

  • Series Title: Mathematics and Visualization

  • DOI: https://doi.org/10.1007/978-1-4471-6497-5

  • Publisher: Springer London

  • eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)

  • Copyright Information: Springer-Verlag London 2014

  • Hardcover ISBN: 978-1-4471-6496-8Published: 30 September 2014

  • Softcover ISBN: 978-1-4471-7104-1Published: 27 September 2016

  • eBook ISBN: 978-1-4471-6497-5Published: 18 September 2014

  • Series ISSN: 1612-3786

  • Series E-ISSN: 2197-666X

  • Edition Number: 1

  • Number of Pages: XVII, 400

  • Number of Illustrations: 10 b/w illustrations, 107 illustrations in colour

  • Topics: Visualization, Computer Imaging, Vision, Pattern Recognition and Graphics, Computer Graphics

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