Shape analysis based on depth-ordering.
Shape analysis based on depth-ordering.
复制标题
基于深度排序的形状分析。
DOI：
10.1016/j.media.2015.04.004
复制
发表时间：
2015
影响因子：
10.9
通讯作者：
Bouix,Sylvain
中科院分区：
文献类型：
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作者：
Hong,Yi;Gao,Yi;Niethammer,Marc;Bouix,Sylvain
在本文中，我们提出了一种新的方法进行形状分析的基础上使用频带深度的形状排序。我们使用这个波段深度来非参数化地定义形状相对于参考人群的全局深度，通常由正常对照受试者组成。这使我们能够在全球范围内量化“正态性”方面的差异。使用形状的深度排序还允许通过使用形状的α中心值来检测局部形状差异。我们提出排列测试，以统计评估全球和局部形状的差异。我们进一步确定形状差异的方向性（局部膨胀与收缩）。该方法的综合生成的纹状体数据集上进行评估，并应用于检测形状的差异，在海马与首发精神分裂症和正常对照组之间的主题。
In this paper we propose a new method for shape analysis based on the ordering of shapes using band-depth. We use this band-depth to non-parametrically define a global depth for a shape with respect to a reference population, typically consisting of normal control subjects. This allows us to globally quantify differences with respect to “normality”. Using the depth-ordering of shapes also allows the detection of localized shape differences by usingα-central values of shapes. We propose permutation tests to statistically assess global and local shape differences. We further determine the directionality of shape differences (local inflation versus deflation). The method is evaluated on a synthetically generated striatum dataset, and applied to detect shape differences in the hippocampus between subjects with first-episode schizophrenia and normal controls.