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Automated multi-atlas labeling of the fornix and its integrity in alzheimer's disease

机译:自动化的多标签标记穹窿标记及其在阿尔茨海默病的完整性

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Alzheimer's disease is the most common form of dementia. Diffusion imaging provides information on white matter integrity not available with standard MRI, revealing additional information on how Alzheimer's disease affects the brain. Here we implemented and tested a multi-atlas labeling algorithm to segment the fornix and a point-correspondence tract matching scheme to assess fiber integrity in the fornix in diffusion MRI from 210 participants scanned as part of the Alzheimer's Disease Neuroimaging Initiative. Various diffusion-derived measures were used to relate fornix degeneration to cognitive decline. On 3D parametric tract models, mean diffusivity (MD) was more sensitive to group differences than fractional anisotropy (FA). Compared to previous studies, we mapped diffusion information along the fornix, yielding 3-D maps of degenerative changes along the tract in people with different stages of Alzheimer's disease.
机译:阿尔茨海默病是最常见的痴呆形式。扩散成像提供有关标准MRI不可用的白质诚信的信息,揭示了阿尔茨海默病如何影响大脑的额外信息。在这里,我们实施并测试了一个多标记标记算法,以分割穹窿和点对应道匹配方案,以评估穹窿中的光纤完整性在分散MRI中,从210名参与者扫描,作为阿尔茨海默病神经影像序列的一部分。各种扩散衍生的措施用于将Fornix变性与认知下降相关。在3D参数道模型上,平均扩散性(MD)对组差异比分数各向异性(FA)更敏感。与以前的研究相比,我们沿穹窿映射了扩散信息,沿着阿尔茨海默病不同阶段的人们施用了沿着多个阶段的道路的下降变化的3D地图。

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