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Metrics for Uncertainty Analysis and Visualization of Diffusion Tensor Images

机译:扩散张量图像的不确定度分析和可视化指标

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In this paper, we propose three metrics to quantify the differences between the results of diffusion tensor magnetic resonance imaging (DT-MRI) fiber tracking algorithms: the area between corresponding fibers of each bundle, the Earth Mover's Distance (EMD) between two fiber bundle volumes, and the current distance between two fiber bundle volumes. We also discuss an interactive fiber track comparison visualization toolkit we have developed based on the three proposed fiber difference metrics and have tested on six widely-used fiber tracking algorithms. To show the effectiveness and robustness of our metrics and visualization toolkit, we present results on both synthetic data and high resolution monkey brain DT-MRI data. Our toolkit can be used for testing the noise effects on fiber tracking analysis and visualization and to quantify the difference between any pair of DT-MRI techniques, compare single subjects within an image atlas.
机译:在本文中,我们提出了三种度量标准来量化扩散张量磁共振成像(DT-MRI)纤维跟踪算法的结果之间的差异:每束相应纤维之间的面积,两根纤维束之间的地球移动者距离(EMD)体积,以及两个纤维束体积之间的当前距离。我们还将讨论基于三个提议的光纤差异度量标准开发的交互式光纤轨迹比较可视化工具包,并已对六种广泛使用的光纤跟踪算法进行了测试。为了显示我们的指标和可视化工具包的有效性和鲁棒性,我们在合成数据和高分辨率猴脑DT-MRI数据上都给出了结果。我们的工具包可用于测试对光纤跟踪分析和可视化的噪声影响,并量化任何一对DT-MRI技术之间的差异,比较图像集内的单个对象。

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