Visualizing Propagator-Based Diffusion Imaging Data

可视化基于传播器的扩散成像数据

• 批准号: 422414649
• 负责人: Professor Dr.-Ing. Thomas Schultz
• 金额: --
• 依托单位: Abteilung III: Neuropädiatrie, Entwicklungsneurologie, Sozialpädiatrie
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2019
• 资助国家: 德国
• 起止时间: 2018-12-31 至 2022-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/422414649?language=en
• 关键词: Visualizing; Propagator; Based; Diffusion; Imaging

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.

扩散磁共振成像及其许多变体在研究和临床上都被牢固地确立用于对人脑的白色物质进行成像。近年来，技术进步使得测量扩散变得越来越可行，不仅具有高角分辨率，而且还具有不同强度的扩散加权。这使得可以估计三维扩散传播因子，其包含关于组织微结构的附加信息。然而，很少有方法来可视化这种复杂的数据存在。我们的项目将首先通过实现适用于高效数据存储、插值和特征提取的表示，为交互式扩散传播算子可视化奠定基础。在此基础上，我们将设计和实现可视化技术在增加空间尺度：从局部（字形）到个体解剖结构（纤维束成像）和全局结构（直接体绘制）。这些方法的灵感来自已成功用于可视化扩散张量场的技术。然而，额外的径向和高角分辨率的扩散传播将需要大量的扩展。我们将特别注意考虑到我们的技术的不确定性和适用性的合奏和比较可视化。最后，我们将与临床合作伙伴密切合作，在真实数据上测试我们的技术。