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Multi-Modal Visualization of Probabilistic Tractography

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Visualization in Medicine and Life Sciences III

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

Abstract

Neuroscientists use visualizations of diffusion data to analyze neural tracts of the brain. More specifically, probabilistic tractography algorithms are a group of methods that reconstruct tract information in diffusion data and need proper visualization. One problem neuroscientists are facing with probabilistic data is putting this information into context. Neuroscience experts already successfully utilized several techniques together with structural MRI to detect neural tracts in the living human brain which were previously only known from tracer studies in macaque monkeys. Whereas the combination with structural MRI, i.e., T1 and T2 images, has been important for these studies, new challenges ask for an integration of other imaging modalities. First, we provide an overview of the currently used visualization techniques. Then, we show how probabilistic tractography can be combined with other techniques, trying to find new and useful visualizations for multi-modal data.

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Acknowledgements

The authors thank the OpenWalnut project [18] for providing the software framework supporting neuroscience visualization and for distributing the Fiber Stipple source code. The software platform was used for conducting this study. We thank C. Heine and A. Wiebel for the fruitful discussions and for commenting on drafts of this article. Last but not least we want to thank the reviewers which gave us very helpful comments and advises.

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Authors and Affiliations

  1. Leipzig University, Leipzig, Germany

    Mathias Goldau & Mario Hlawitschka

  2. Max-Planck-Institute for Neurological Research, Cologne, Germany

    Mathias Goldau

Authors
  1. Mathias Goldau
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  2. Mario Hlawitschka
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Corresponding authors

Correspondence to Mathias Goldau or Mario Hlawitschka .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Elect, Jacobs University, Bremen, Germany

    Lars Linsen

  2. Department of Computer Science, University of California, Davis, California, USA

    Bernd Hamann

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

    Hans-Christian Hege

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Goldau, M., Hlawitschka, M. (2016). Multi-Modal Visualization of Probabilistic Tractography. In: Linsen, L., Hamann, B., Hege, HC. (eds) Visualization in Medicine and Life Sciences III. Mathematics and Visualization. Springer, Cham. https://doi.org/10.1007/978-3-319-24523-2_9

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