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DTI based structural damage characterization for Disorders of Consciousness

机译:基于DTI的意识障碍的结构损伤表征

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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 brain damages. The main idea is to perform a water diffusivity estimation in the damaged tissue by weighting and combining differently each tensor orthogonal strength. Using these new scalar quantities we constructed an affine invariant DTI tensor feature based on regional tissue histograms that outperforms state-of-the-art tensor based scalar representations for discrimination problems.
机译:MRI扩散张量成像(DTI)最近已被提出作为一种高度判别性的测量方法,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聚合(GOWA)的新标量量族,以表征形态学上的脑损伤。主要思想是通过加权和不同地组合每个张量正交强度来在受损组织中执行水扩散率估计。使用这些新的标量,我们基于区域组织直方图构造了仿射不变DTI张量特征,该特征优于针对歧视问题的基于最新张量的标量表示形式。

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