Diffusion-Based Tractography: Visualizing Dense White Matter Connectivity from 3D Tensor Fields
Diffusion-Based Tractography: Visualizing Dense White Matter Connectivity from 3D Tensor Fields
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DOI：
10.2312/vg/vg06/119-126
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发表时间：
2006
期刊：
影响因子：
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通讯作者：
S. Muraki;I. Fujishiro;Yasuko Suzuki;Yuriko Takeshima
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文献类型：
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作者：
S. Muraki;I. Fujishiro;Yasuko Suzuki;Yuriko Takeshima
在本文中，我们提出了一种称为基于扩散的纤维束成像（DBT）的新颖方法，用于可视化扩散张量磁共振成像数据集。 DBT方法通过涂抹3D随机点纹理来生成类似于线积分卷积（LIC）的3D纹理。与仅追踪单个方向的 LIC 方法相比，DBT 方法同时考虑线性和平面扩散分量，并通过分析三个分解分量来抑制过度模糊。我们将证明 DBT 方法对于从 3D 扩散张量场可视化密集的白质连接是有效的，并且它适合使用商用图形处理器进行硬件加速。
In this paper, we present a novel method, called diffusion-based tractography (DBT), for visualizing diffusion tensor magnetic resonance imaging datasets. The DBT method generates 3D textures similar to the line integral convolution (LIC) by smearing 3D random dot textures. In contrast to the LIC method, which only traces a single direction, the DBT method takes into account both linear and planar diffusion components, and suppresses excessive blur by an analysis of three decomposed components. We will demonstrate that the DBT method is effective for visualizing dense white matter connectivity from 3D diffusion tensor fi elds and that it is suitable for hardware acceleration using commodity graphics processors.