Visualization in Medicine and Life Sciences II

1. Front Matter

   Pages i-viii

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2. Feature Extraction

   1. Front Matter

      Pages 1-1

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   2. Discrete Distortion for 3D Data Analysis

      • Leila De Floriani, Federico Iuricich, Paola Magillo, Mohammed Mostefa Mesmoudi, Kenneth Weiss

      Pages 3-25

   3. Interactive Visualization–A Key Prerequisite for Reconstruction and Analysis of Anatomically Realistic Neural Networks

      • Vincent J. Dercksen, Marcel Oberlaender, Bert Sakmann, Hans-Christian Hege

      Pages 27-44

   4. MRI-Based Visualisation and Quantification of Rheumatoid and Psoriatic Arthritis of the Knee

      • Ben Donlon, Douglas Veale, Patrick Brennan, Robert Gibney, Hamish Carr, Louise Rainford et al.

      Pages 45-59

   5. An Application for the Visualization and Quantification of HIV-Associated Lipodystrophy from Magnetic Resonance Imaging Datasets

      • Tadhg O’Sullivan, Patrick Brennan, Peter Doran, Paddy Mallon, Stephen J. Eustace, Eoin Kavannagh et al.

      Pages 61-68

3. Classification

   1. Front Matter

      Pages 69-69

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   2. Semi-Automatic Rough Classification of Multichannel Medical Imaging Data

      • Ahmed Elmoasry, Mohamed Sadek Maswadah, Lars Linsen

      Pages 71-89

   3. An Evaluation of Peak Finding for DVR Classification of Biological Data

      • Aaron Knoll, Rolf Westerteiger, Hans Hagen

      Pages 91-106

4. Volumes and Shapes

   1. Front Matter

      Pages 107-107

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   2. Vessel Visualization with Volume Rendering

      • Christoph Kubisch, Sylvia Glaßer, Mathias Neugebauer, Bernhard Preim

      Pages 109-132

   3. Efficient Selection of Representative Views and Navigation Paths for Volume Data Exploration

      • Eva Monclús, Pere-Pau Vázquez, Isabel Navazo

      Pages 133-151

   4. Feature Preserving Smoothing of Shapes Using Saliency Skeletons

      • Alexandru Telea

      Pages 153-170

5. Tensor Visualization

   1. Front Matter

      Pages 171-171

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   2. Enhanced DTI Tracking with Adaptive Tensor Interpolation

      • Alessandro Crippa, Andrei C. Jalba, Jos B. T. M. Roerdink

      Pages 173-190

   3. Image-Space Tensor Field Visualization Using a LIC-like Method

      • Sebastian Eichelbaum, Mario Hlawitschka, Bernd Hamann, Gerik Scheuermann

      Pages 191-208

   4. Towards a High-quality Visualization of Higher-order Reynold’s Glyphs for Diffusion Tensor Imaging

      • Mario Hlawitschka, Younis Hijazi, Aaron Knoll, Bernd Hamann

      Pages 209-225

6. Visualizing Genes, Proteins, and Molecules

   1. Front Matter

      Pages 227-227

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   2. VENLO: Interactive Visual Exploration of Aligned Biological Networks and Their Evolution

      • Steffen Brasch, Georg Fuellen, Lars Linsen

      Pages 229-247

   3. Embedding Biomolecular Information in a Scene Graph System

      • Andreas Halm, Eva Eggeling, Dieter W. Fellner

      Pages 249-264

For some time, medicine has been an important driver for the development of data processing and visualization techniques. Improved technology offers the capacity to generate larger and more complex data sets related to imaging and simulation. This, in turn, creates the need for more effective visualization tools for medical practitioners to interpret and utilize data in meaningful ways. The first edition of Visualization in Medicine and Life Sciences (VMLS) emerged from a workshop convened to explore the significant data visualization challenges created by emerging technologies in the life sciences. The workshop and the book addressed questions of whether medical data visualization approaches can be devised or improved to meet these challenges, with the promise of ultimately being adopted by medical experts. Visualization in Medicine and Life Sciences II follows the second international VMLS workshop, held in Bremerhaven, Germany, in July 2009. Internationally renowned experts from the visualization and driving application areas came together for this second workshop. The book presents peer-reviewed research and survey papers which document and discuss the progress made, explore new approaches to data visualization, and assess new challenges and research directions.

• information visualization
• medical visualization
• visualization in bioinformatics
• visualization in life sciences
• volume visualization

From the reviews:

“The book is a collection of fifteen articles covering a broad range of topics related to visualization in medicine and life sciences. … The book in itself gives good references about state-of-the-art issues or software or methodologies, even though they are mostly European-centered. … It is worth reading this kind of review for researchers interested in broadening their understanding of the upcoming needs of visualization for life science or for graduate students to understand the new challenges at the crossroads of computer and life sciences.” (Nicolas Loménie, IAPR Newsletter, Vol. 35 (2), April, 2013)

• Bremen School of Engineering and Science, Jacobs University, Bremen, Germany

  Lars Linsen

• FB Informatik, Universität Kaiserslautern, Kaiserslautern, Germany

  Hans Hagen

• Institute for Data Analysis and Visualization Department of Computer Science, University of California, Davis, Davis, USA

  Bernd Hamann

• Visualization and Data Analysis, Zuse Institute Berlin (ZIB), Berlin, Germany

  Hans-Christian Hege

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