Visualizing Propagator-Based Diffusion Imaging Data

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Diffusion Magnetic Resonance Imaging and its many variants are firmly established for imaging the white matter of the human brain, both in research and in the clinic. In recent years, technical progress has increasingly made it feasible to measure diffusion not just with high angular resolution, but in addition with varying strengths of diffusion weighting. This makes it possible to estimate a three-dimensional diffusion propagator, which contains additional information about tissue microstructure. However, very few approaches to visualizing this intricate data exist. Our project will first lay the foundation for interactive diffusion propagator visualization by implementing representations that are suitable for efficient data storage, interpolation, and feature extraction. Building on this, we will design and implement visualization techniques at increasing spatial scales: From local (glyphs) to individual anatomical structures (tractography) and global structures (direct volume rendering). These methods are inspired by techniques that have been successfully used for visualizing diffusion tensor fields. However, the additional radial and the high angular resolution of diffusion propagators will require substantial extensions. We will pay special attention to account for uncertainty and suitability of our techniques for ensemble and comparative visualization. Finally, we will test our techniques on real-world data in close collaboration with a clinical partner.