MRI Diffusion Tensor Imaging (DTI) has been recently proposed as a highly discriminative measurement to detect structural damages in Disorders of Consciousness patients (Vegetative State/Unresponsive Wakefulness Syndrome-(VS/UWS) and Minimally Consciousness State-MCS). In the DTI analysis, certain tensor features are often used as simplified scalar indices to represent these alterations. Those characteristics are mathematically and statistically more tractable than the full tensors. Nevertheless, most of these quantities are based on a tensor diffusivity estimation, the arithmetic average among the different strengths of the tensor orthogonal directions, which is supported on a symmetric linear relationship among the three directions, an unrealistic assumption for severely damaged brains. In this paper, we propose a new family of scalar quantities based on Generalized Ordered Weighted Aggregations (GOWA) to characterize morphological damages. The main idea is to compute a tensor diffusitivity estimation that captures the deviations in the water diffusivity associated to damaged tissue. This estimation is performed by weighting and combining differently each tensor orthogonal strength. Using these new scalar quantities we construct an affine invariant DTI tensor feature using regional tissue histograms. An evaluation of these new scalar quantities on 48 patients (23 VS/UWS and 25 MCS) was conducted. Our experiments demonstrate that this new representation outperforms state-of-the-art tensor based scalar representations for characterization and classification problems.
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机译:MRI弥散张量成像(DTI)最近已被提出作为一种高判别性测量方法,用于检测意识障碍患者(植物性状态/无反应清醒综合征(VS / UWS)和最低意识状态-MCS)中的结构损伤。在DTI分析中,某些张量特征通常用作简化的标量索引来表示这些变化。这些特征在数学和统计上比完整张量更易于处理。然而,这些量中的大多数是基于张量扩散率估计的,即张量正交方向不同强度之间的算术平均值,这由三个方向之间的对称线性关系支持,对于严重受损的大脑来说这是不现实的假设。在本文中,我们提出了一个基于广义有序加权集合(GOWA)的新标量数量族,以表征形态损伤。主要思想是计算张量扩散率估计值,该估计值可捕获与受损组织相关的水扩散率偏差。通过对每个张量正交强度进行加权和不同组合来执行此估计。使用这些新的标量,我们使用区域组织直方图构造仿射不变DTI张量特征。对48位患者(23 VS / UWS和25 MCS)的这些新标量进行了评估。我们的实验表明,对于表征和分类问题,此新表示优于基于张量的最新标量表示。
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