Confidence mapping in diffusion tensor magnetic resonance imaging tractography using a bootstrap approach
Confidence mapping in diffusion tensor magnetic resonance imaging tractography using a bootstrap approach
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DOI：
10.1002/mrm.20466
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发表时间：
2005-05-01
影响因子：
3.3
通讯作者：
Pierpaoli, C
中科院分区：
文献类型：
--
作者：
Jones, DK;Pierpaoli, C
自举技术是一种非常强大的非参数统计方法，用于确定给定统计量中的不确定性。然而，它在扩散张量MRI束状图中的应用实际上尚未被探索。这项工作显示了如何使用自举来为确定性跟踪算法获得的结果分配置信度。通过调用“通道传播器”的概念，它还强调了本地光纤体系结构或体系结构环境对跟踪再现性的重要影响。最后，讨论了该技术的实际优点和局限性。bootstrap不仅允许以概率方式使用任何确定性的轨迹图算法，而且它的无模型包含所有可变性源（包括那些不能建模的）意味着它提供了最现实的概率轨迹图方法。中华医学杂志（英文版），2005。2005年Wiley-Liss出版。
The bootstrap technique is an extremely powerful nonparametric statistical procedure for determining the uncertainty in a given statistic. However, its use in diffusion tensor MRI tractography remains virtually unexplored. This work shows how the bootstrap can be used to assign confidence to results obtained with deterministic tracking algorithms. By invoking the concept of a "tract-propagator," it also underlines the important effect of local fiber architecture or architectural milieu on tracking reproducibility. Finally, the practical advantages and limitations of the technique are discussed. Not only does the bootstrap allow any deterministic tractography algorithm to be used in a probabilistic fashion, but also its model-free inclusion of all sources of variability (including those that cannot be modeled) means that it provides the most realistic approach to probabilistic tractography. Magn Pleson Med 53:1143-1149, 2005. Published 2005 Wiley-Liss, Inc.