{"title":"基于流动的纤维方向分布函数几何插值。","authors":"Xinyu Nie, Yonggang Shi","doi":"10.1007/978-3-031-43993-3_5","DOIUrl":null,"url":null,"abstract":"<p><p>The fiber orientation distribution function (FOD) is an advanced model for high angular resolution diffusion MRI representing complex fiber geometry. However, the complicated mathematical structures of the FOD function pose challenges for FOD image processing tasks such as interpolation, which plays a critical role in the propagation of fiber tracts in tractography. In FOD-based tractography, linear interpolation is commonly used for numerical efficiency, but it is prone to generate false artificial information, leading to anatomically incorrect fiber tracts. To overcome this difficulty, we propose a flowbased and geometrically consistent interpolation framework that considers peak-wise rotations of FODs within the neighborhood of each location. 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引用次数: 0
摘要
纤维取向分布函数(FOD)是一种先进的高角度分辨率扩散核磁共振成像模型,代表了复杂的纤维几何形状。然而,FOD 函数复杂的数学结构给 FOD 图像处理任务(如插值)带来了挑战,而插值在束流成像中纤维束的传播中起着至关重要的作用。在基于 FOD 的纤维束成像中,线性插值通常用于提高数值效率,但它容易产生虚假的人工信息,导致解剖学上不正确的纤维束。为了克服这一困难,我们提出了一种基于流的几何一致性插值框架,该框架考虑了每个位置邻域内 FOD 的峰值旋转。我们的方法将 FOD 函数分解为多个分量,并使用平滑矢量场对其邻域内每个峰值的流量进行建模。为了沿着每个矢量场的流向生成插值结果,我们开发了一种闭式高效方法来旋转邻近体素中的 FOD 峰,并实现 FOD 分量的几何一致性插值。通过合并每个峰值的插值结果,我们得到了最终的 FOD 插值结果。人类连接组计划(HCP)数据的实验结果表明,我们的方法产生的 FOD 插值在解剖学上更有意义,并显著提高了牵引成像的性能。
Flow-based Geometric Interpolation of Fiber Orientation Distribution Functions.
The fiber orientation distribution function (FOD) is an advanced model for high angular resolution diffusion MRI representing complex fiber geometry. However, the complicated mathematical structures of the FOD function pose challenges for FOD image processing tasks such as interpolation, which plays a critical role in the propagation of fiber tracts in tractography. In FOD-based tractography, linear interpolation is commonly used for numerical efficiency, but it is prone to generate false artificial information, leading to anatomically incorrect fiber tracts. To overcome this difficulty, we propose a flowbased and geometrically consistent interpolation framework that considers peak-wise rotations of FODs within the neighborhood of each location. Our method decomposes a FOD function into multiple components and uses a smooth vector field to model the flows of each peak in its neighborhood. To generate the interpolated result along the flow of each vector field, we develop a closed-form and efficient method to rotate FOD peaks in neighboring voxels and realize geometrically consistent interpolation of FOD components. By combining the interpolation results from each peak, we obtain the final interpolation of FODs. Experimental results on Human Connectome Project (HCP) data demonstrate that our method produces anatomically more meaningful FOD interpolations and significantly enhances tractography performance.