A filtered approach to neural tractography using the Watson directional function.
A filtered approach to neural tractography using the Watson directional function.
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DOI：
10.1016/j.media.2009.10.003
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发表时间：
2010-02
影响因子：
10.9
通讯作者：
Rathi, Yogesh
中科院分区：
文献类型：
--
作者：
Malcolm, James G.;Michailovich, Oleg;Bouix, Sylvain;Westin, Carl-Fredrik;Shenton, Martha E.;Rathi, Yogesh
我们提出了一种同时估计局部纤维方向并进行多纤维纤维束成像的技术。现有技术独立地估计每个体素处的局部纤维取向，因此没有关于测量信号或估计纤维取向的置信度的运行知识。此外，为了克服噪声，许多算法使用滤波器作为后处理步骤来获得平滑的轨迹。我们将光纤跟踪表述为因果估计：在跟踪光纤的每个步骤中，信号的当前估计由前一个估计引导。为此，我们将信号建模为 Watson 方向函数的离散混合，并在过滤框架内执行纤维束成像。从种子点开始，使用无迹卡尔曼滤波器将每根光纤追踪到其终端，以同时拟合信号并以最一致的方向传播。尽管存在噪声和不确定性，但这提供了对光纤沿线每个点的局部结构的准确估计。我们选择 Watson 函数，因为它提供了由主扩散方向和描述各向异性的缩放参数参数化的信号的紧凑表示，并且还允许根据这些参数分析重建定向扩散函数。使用两种和三种成分的混合（对应于两光纤和三光纤模型），我们在合成实验中证明，这种方法减少了信号重建误差，并显着提高了交叉和分支处的角分辨率。体内实验检查胼胝体和内囊，并确认追踪已知包含此类交叉和分支的区域的能力，同时提供固有的路径正则化。
We propose a technique to simultaneously estimate the local fiber orientations and perform multi-fiber tractography. Existing techniques estimate the local fiber orientation at each voxel independently so there is no running knowledge of confidence in the measured signal or estimated fiber orientation. Further, to overcome noise, many algorithms use a filter as a post-processing step to obtain a smooth trajectory. We formulate fiber tracking as causal estimation: at each step of tracing the fiber, the current estimate of the signal is guided by the previous. To do this, we model the signal as a discrete mixture of Watson directional functions and perform tractography within a filtering framework. Starting from a seed point, each fiber is traced to its termination using an unscented Kalman filter to simultaneously fit the signal and propagate in the most consistent direction. Despite the presence of noise and uncertainty, this provides an accurate estimate of the local structure at each point along the fiber. We choose the Watson function since it provides a compact representation of the signal parameterized by the principal diffusion direction and a scaling parameter describing anisotropy, and also allows analytic reconstruction of the oriented diffusion function from those parameters. Using a mixture of two and three components (corresponding to two-fiber and three-fiber models) we demonstrate in synthetic experiments that this approach reduces signal reconstruction error and significantly improves the angular resolution at crossings and branchings. In vivo experiments examine the corpus callosum and internal capsule and confirm the ability to trace through regions known to contain such crossing and branching while providing inherent path regularization.
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