基于体素的解剖神经影像数据分析与分类的特征比较

Anne-Laure Fouque, C. Fischer, V. Frouin, P. Ciuciu, E. Duchesnay
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引用次数: 1

摘要

本文的目的是确定相关特征,以提高对每个受试者的结构(t1加权)MRI与组(临床状态)之间关联的识别。我们在模拟和实验数据上比较了从灰质和变形中得到的5个特征。使用基于体素的分析,我们比较了检测解剖差异的敏感性,使用模式识别方法,我们比较了群体预测的准确性。我们的数据的最佳结果是通过变形的多元表示,应变张量,可以与灰质相关联。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison of Features for Voxel-Based Analysis and Classification of Anatomical Neuroimaging Data
The aim of this paper is to identify the relevant features that improve the identification of associations between structural (T1-weighted) MRI and a group (clinical status) of each subject. We compare 5 features derived from grey matter and deformation, on both simulated and experimental data. With voxel-based analysis we compare sensitivity of detection of anatomical differences, with pattern recognition approaches, we compare the accuracies of group prediction. The best results on our data are achieved by a multivariate representation of the deformation, the strain tensor, that can be associated with grey matter.
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