Zhou Luping, Lieby Paulette, Barnes Nick, Réglade-Meslin Chantal, Walker Janine, Cherbuin Nicolas, Hartley Richard
RSISE, Australian National University, Canberra, Australia.
Hippocampus. 2009 Jun;19(6):533-40. doi: 10.1002/hipo.20639.
In this article, we present a framework to perform statistical shape analysis for segmented hippocampi, including an efficient permutation test for detecting subtle class differences, and a regularized discriminative direction method for visualizing the shape discrepancy. Fisher permutation and bootstrap tests are preferred to traditional hypothesis tests which impose assumptions on the distribution of the samples. In this article, an efficient algorithm is adopted to rapidly perform the exact tests. We extend this algorithm to multivariate data by projecting the shape descriptors onto an informative direction that preserves the original discriminative information as much as possible to generate a scalar test statistic. This informative direction is further used to seek a discriminative direction to isolate the discriminative shape difference between classes from the individual variability. Compared with existing methods, the discriminative direction used in this article is regularized by requiring that the shapes deformed along it respect the underlying shape distribution as well as reflecting the essential shape differences between two populations. Hence, a more accurate localization of difference is produced. We apply our methods to analyze the hippocampal shapes for controls and subjects with Alzheimer's disease from the publicly available OASIS MRI database. We show how to localize the shape differences between the two classes.
在本文中，我们提出了一个用于对分割后的海马体进行统计形状分析的框架，包括一种用于检测细微类别差异的高效置换检验，以及一种用于可视化形状差异的正则化判别方向方法。相较于对样本分布进行假设的传统假设检验，费舍尔置换检验和自助法检验更受青睐。在本文中，采用了一种高效算法来快速执行精确检验。我们通过将形状描述符投影到一个尽可能保留原始判别信息的信息方向上，将该算法扩展到多变量数据，以生成一个标量检验统计量。这个信息方向进一步用于寻找一个判别方向，以从个体变异性中分离出类别之间的判别形状差异。与现有方法相比，本文中使用的判别方向通过要求沿其变形的形状既尊重潜在形状分布又反映两个群体之间的本质形状差异来进行正则化。因此，能够更准确地定位差异。我们应用我们的方法来分析来自公开可用的OASIS MRI数据库中的对照组和阿尔茨海默病患者的海马体形状。我们展示了如何定位这两个类别之间的形状差异。
