使用空间相干归一化割算法的神经元白质分割
NEURONAL WHITE MATTER PARCELLATION USING SPATIALLY COHERENT NORMALIZED CUTS.
作者信息
Bloy Luke, Ingalhalikar Madhura, Verma Ragini
机构信息
Department of Bioengineering, University of Pennsylvania.
出版信息
Proc IEEE Int Symp Biomed Imaging. 2011:2061-2065. doi: 10.1109/ISBI.2011.5872818.
This work presents an automated method for partitioning neuronal white matter (WM) into regions of interest with uniform WM architecture. These regions can then be used to replace atlas-derived regions for any subsequent statistical analysis. The fiber orientation distribution function is used as a model of WM architecture resulting in a voxel similarity function sensitive to both fiber orientations and configurations. The method utilizes the normalized cuts algorithm to partition WM voxels based on this similarity function along with a connected component labeling algorithm to ensure spatial compactness. We illustrate the algorithms ability to discern regions based on both orientation and complexity through its application to a simulated fiber crossing and an in-vivo dataset.
这项工作提出了一种自动方法，用于将神经元白质（WM）划分为具有统一WM结构的感兴趣区域。然后，这些区域可用于替代图谱衍生区域，以进行任何后续的统计分析。纤维取向分布函数被用作WM结构的模型，从而产生一个对纤维取向和配置都敏感的体素相似性函数。该方法利用归一化切割算法基于此相似性函数对WM体素进行划分，并结合连通分量标记算法以确保空间紧凑性。我们通过将算法应用于模拟纤维交叉和体内数据集，展示了其基于取向和复杂性辨别区域的能力。
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