Estimating Crossing Fibers: A Tensor Decomposition Approach
Estimating Crossing Fibers: A Tensor Decomposition Approach
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DOI：
10.1109/tvcg.2008.128
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发表时间：
2008-11-01
影响因子：
5.2
通讯作者：
Seidel, Hans-Peter
中科院分区：
文献类型：
--
作者：
Schultz, Thomas;Seidel, Hans-Peter
磁共振扩散加权成像是一种独特的工具，非侵入性调查的主要神经纤维束。由于流行的扩散张量（DT-MRI）模型仅限于具有单个纤维方向的体素，因此已经提出了许多高角分辨率技术来提供关于更多样化的纤维分布的信息。两种这样的方法是O-Ball成像和球面反卷积，其在球面上产生取向分布函数（ODF）。为了分析和可视化，这些函数的最大值已用作主要方向，尽管已知在交叉纤维束的情况下结果会有偏差。在本文中，我们提出了一个更可靠的技术，从连续ODF，这是基于分解成一个各向同性的组件，几个秩1项，和一个小的残差的高阶张量表示提取离散方向。与合成数据中的地面实况相比，该新方法减少了偏差，并可靠地重建了未被解析为ODF中的个体最大值的交叉纤维。我们目前的结果O-球和球面反卷积数据，并证明，估计的方向允许合理的纤维跟踪在一个真实的数据集。
Diffusion weighted magnetic resonance imaging is a unique tool for non-invasive investigation of major nerve fiber tracts. Since the popular diffusion tensor (DT-MRI) model is limited to voxels with a single fiber direction, a number of high angular resolution techniques have been proposed to provide information about more diverse fiber distributions. Two such approaches are O-Ball imaging and spherical deconvolution, which produce orientation distribution functions (ODFs) on the sphere. For analysis and visualization, the maxima of these functions have been used as principal directions, even though the results are known to be biased in case of crossing fiber tracts. In this paper, we present a more reliable technique for extracting discrete orientations from continuous ODFs, which is based on decomposing their higher-order tensor representation into an isotropic component, several rank-1 terms, and a small residual. Comparing to ground truth in synthetic data shows that the novel method reduces bias and reliably reconstructs crossing fibers which are not resolved as individual maxima in the ODF. We present results on both O-Ball and spherical deconvolution data and demonstrate that the estimated directions allow for plausible fiber tracking in a real data set.