Mathias Goldau, Alexander Wiebel, Mario Hlawitschka, Gerik Scheuermann, and Marc Tittgemeyer
Medical Imaging, Surface Modeling, Fiber Bundles, Diffusion MRI
Diffusion magnetic resonance imaging is so far the only medical imaging modality that has the potential for probing anatomical brain connectivity in vivo. Specifically, it provides the data basis for a set of techniques allowing for tracking of fiber bundles in the brain's white matter. Furthermore, due to the micro-structural basis of the diffusion process, fiber integrity might be estimated. Typically, this is achieved by tensor-derived parameters, such as by fractional anisotropy (FA), which allows for a quantification of the directionality of local diffusion properties. In neuroscience, such parameterization of the diffusion tensor has greatly stimulated studies of localized brain changes, related to development, aging, or various neurological and psychiatric diseases. However, thus far, there is no satisfactory solution for the visualization and assessment of such parameters along fiber bundles. In this paper, we present a novel technique to visualize changes of tensor-derived parameters along clusters of the trajectories obtained from diffusion tractography. This visualization approach consists of two steps: First, an automatic local aggregation of data values around the trajectories for quantitative analysis and visualization on the fiber bundle boundary and second, a color-coded slice that is intuitively movable along the bundle for interactive exploration of the bundle's parameters.
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