Biomedical Image Analysis Group, Department of Biomedical Engineering, Technische Universiteit Eindhoven, MB 5600, Eindhoven, The Netherlands.
IEEE Trans Vis Comput Graph. 2011 Oct;17(10):1407-19. doi: 10.1109/TVCG.2010.244.
High-angular resolution diffusion imaging (HARDI) is a diffusion weighted MRI technique that overcomes some of the decisive limitations of its predecessor, diffusion tensor imaging (DTI), in the areas of composite nerve fiber structure. Despite its advantages, HARDI raises several issues: complex modeling of the data, nonintuitive and computationally demanding visualization, inability to interactively explore and transform the data, etc. To overcome these drawbacks, we present a novel, multifield visualization framework that adopts the benefits of both DTI and HARDI. By applying a classification scheme based on HARDI anisotropy measures, the most suitable model per imaging voxel is automatically chosen. This classification allows simplification of the data in areas with single fiber bundle coherence. To accomplish fast and interactive visualization for both HARDI and DTI modalities, we exploit the capabilities of modern GPUs for glyph rendering and adopt DTI fiber tracking in suitable regions. The resulting framework, allows user-friendly data exploration of fused HARDI and DTI data. Many incorporated features such as sharpening, normalization, maxima enhancement and different types of color coding of the HARDI glyphs, simplify the data and enhance its features. We provide a qualitative user evaluation that shows the potentials of our visualization tools in several HARDI applications.
高角度分辨率扩散成像（HARDI）是一种扩散加权 MRI 技术，它克服了其前身扩散张量成像（DTI）在复合神经纤维结构领域的一些决定性限制。尽管具有优势，但 HARDI 也带来了一些问题：数据的复杂建模、非直观和计算要求高的可视化、无法交互探索和转换数据等。为了克服这些缺点，我们提出了一种新颖的多领域可视化框架，该框架采用了 DTI 和 HARDI 的优势。通过应用基于 HARDI 各向异性测量的分类方案，自动选择每个成像体素最适合的模型。这种分类允许在具有单纤维束相干性的区域简化数据。为了实现 HARDI 和 DTI 模态的快速交互可视化，我们利用现代 GPU 的 glyph 渲染功能，并在适当的区域采用 DTI 纤维跟踪。所得到的框架允许对融合的 HARDI 和 DTI 数据进行用户友好的数据探索。许多集成的功能，如锐化、归一化、最大值增强和 HARDI glyph 的不同类型的颜色编码，简化了数据并增强了其特征。我们提供了定性的用户评估，展示了我们的可视化工具在几个 HARDI 应用中的潜力。
