Illustrative white matter fiber bundles

  • Authors:

  • Ron Otten;Anna Vilanova;Huub van de Wetering

  • Affiliations:

  • Department of Mathematics and Computer Science, Eindhoven University of Technology, The Netherlands;Department of Biomedical Engineering, Eindhoven University of Technology, The Netherlands;Department of Mathematics and Computer Science, Eindhoven University of Technology, The Netherlands

  • Venue:
  • EuroVis'10 Proceedings of the 12th Eurographics / IEEE - VGTC conference on Visualization
  • Year:
  • 2010

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Abstract

Diffusion Tensor Imaging (DTI) has made feasible the visualization of the fibrous structure of the brain white matter. In the last decades, several fiber-tracking methods have been developed to reconstruct the fiber tracts from DTI data. Usually these fiber tracts are shown individually based on some selection criteria like region of interest. However, if the white matter as a whole is being visualized clutter is generated by directly rendering the individual fiber tracts. Often users are actually interested in fiber bundles, anatomically meaningful entities that abstract from the fibers they contain. Several clustering techniques have been developed that try to group the fiber tracts in fiber bundles. However, even if clustering succeeds, the complex nature of white matter still makes it difficult to investigate. In this paper, we propose the use of illustration techniques to ease the exploration of white matter clusters. We create a technique to visualize an individual cluster as a whole. The amount of fibers visualized for the cluster is reduced to just a few hint lines, and silhouette and contours are used to improve the definition of the cluster borders. Multiple clusters can be easily visualized by a combination of the single cluster visualizations. Focus+context concepts are used to extend the multiple-cluster renderings. Exploded views ease the exploration of the focus cluster while keeping the context clusters in an abstract form. Real-time results are achieved by the GPU implementation of the presented techniques.