Virtual Brain

Visualization of Probabilistic Fiber Pathways in Virtual Reality

In collaboration with Tobias Rick, Svenja Caspers, Torsten Kuhlen and Katrin Amunts from the institute of neuroscience and medicine (INM-1 and INM-2) at the Forschungszentrum Jülich.

Understanding the connectivity structure of the human brain is a fundamental prerequisite for the treatment of psychiatric or neurological diseases. Probabilistic tractography has become an established method to account for the inherent uncertainties of the actual course of fiber bundles in magnetic resonance imaging data. This video presents a virtual reality application that addresses the assessment of fiber probabilities in relation to anatomical landmarks. We employ real-time transparent rendering strategy to display fiber tracts within their structural context in a virtual environment. Thereby, we not only emphasize spatial patterns but furthermore allow an interactive control over the amount of visible anatomical information.


  • Svenja Caspers, Simon B. Eickhoff, Tobias Rick, Anette von Kapri, Torsten Kuhlen, Ruiwang Huang, Nadim J. Shah, Karl Zilles
    Probabilistic fibre tract analysis of cytoarchitectonically defined human inferior parietal lobule areas reveals similarities to macaques [pdf] [doi] [bibtex]
    NeuroImage, 2011, Article in Press
  • Tobias Rick, Anette von Kapri, Svenja Caspers, Katrin Amunts, Karl Zilles, Torsten Kuhlen
    Visualization of Probabilistic Fiber Tracts in Virtual Reality [pdf] [doi] [bibtex]
    In proceedings of Medicine Meets Virtual Reality 2011
  • Anette von Kapri, Tobias Rick, Svenja Caspers, Simon B. Eickhoff, Karl Zilles, Torsten Kuhlen
    Evaluating a visualization of uncertainty in probabilistic tractography [pdf] [doi] [bibtex]
    In proceedings of SPIE Medical Imaging 2010: Visualization, Image-Guided Procedures, and Modeling
  • Tobias Rick, Anette von Kapri, Svenja Caspers, Simon B. Eickhoff, Karl Zilles, Torsten Kuhlen
    Poster: Interactive Visualization of Uncertainty in Probabilistic Tractography of Brain’s White Matter Pathways as assessed by Diffusion Tensor Imaging [pdf]
    IEEE Visualization Conference 2009