Jones Derek K, Pierpaoli Carlo
Section on Tissue Biophysics and Biomimetics, Laboratory of Integrative Medicine and Biophysics, National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland, USA.
Magn Reson Med. 2005 May;53(5):1143-9. doi: 10.1002/mrm.20466.
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.
自举技术是一种极其强大的非参数统计程序，用于确定给定统计量的不确定性。然而，它在扩散张量磁共振成像纤维束成像中的应用实际上仍未得到探索。这项工作展示了如何使用自举技术为确定性追踪算法获得的结果赋予置信度。通过引入“纤维束传播器”的概念，它还强调了局部纤维结构或结构环境对追踪可重复性的重要影响。最后，讨论了该技术的实际优点和局限性。自举技术不仅允许以概率方式使用任何确定性纤维束成像算法，而且其无模型地包含所有变异性来源（包括那些无法建模的来源）意味着它为概率性纤维束成像提供了最现实的方法。
