DT-MRI Streamsurfaces Revisited
DT-MRI Streamsurfaces Revisited
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DOI：
10.1109/tvcg.2018.2864845
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发表时间：
2019-01
影响因子：
5.2
通讯作者：
Michael Ankele;T. Schultz
中科院分区：
文献类型：
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作者：
Michael Ankele;T. Schultz
DT-MRI流表面，定义为处处与主特征向量场和中特征向量场相切的表面，已被提出作为扩散张量MRI中主要平面行为区域可视化的工具。尽管人们早就知道它们的构造假设所涉及的特征向量场满足可积条件，但从未系统地测试过该条件是否在实际数据中满足。我们在可视化文献中引入了一个合适且有效的可计算测试，证明了它可以用于区分模拟中的可积和不可积配置，并将其应用于15个健康受试者的全脑数据集。我们得出的结论是，流表面可积性在大脑的很大一部分近似满足，但不是所有地方，包括一些平面区域。因此，流面提取算法应该明确地测试局部可积性。最后，我们提出了一种新颖的基于补丁的流表面可视化方法，该方法减少了视觉伪影，并且可以更充分地采样流表面的范围。
DT-MRI streamsurfaces, defined as surfaces that are everywhere tangential to the major and medium eigenvector fields, have been proposed as a tool for visualizing regions of predominantly planar behavior in diffusion tensor MRI. Even though it has long been known that their construction assumes that the involved eigenvector fields satisfy an integrability condition, it has never been tested systematically whether this condition is met in real-world data. We introduce a suitable and efficiently computable test to the visualization literature, demonstrate that it can be used to distinguish integrable from nonintegrable configurations in simulations, and apply it to whole-brain datasets of 15 healthy subjects. We conclude that streamsurface integrability is approximately satisfied in a substantial part of the brain, but not everywhere, including some regions of planarity. As a consequence, algorithms for streamsurface extraction should explicitly test local integrability. Finally, we propose a novel patch-based approch to streamsurface visualization that reduces visual artifacts, and is shown to more fully sample the extent of streamsurfaces.