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Blood vessel feature description for detection of Alzheimers disease

机译:用于检测阿尔茨海默氏病的血管功能描述

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We describe how image analysis can be used to detect the presence of Alzheimer's disease. The data are images of brain tissue collected from subjects with and without Alzheimer's disease. The analysis concentrates on the shape and structure of the blood vessels which are known to be affected by amyloid beta, whose drainage is affected by Alzheimer's disease. The structure is analysed by a new approach which measures the Influence of the blood vessels' branching structures. Their density and tortuosity are analysed in conjunction with a boundary description derived using Fourier descriptors. These measures form a feature vector which is derived from the images of brain tissue, and the discrimination capability shows that it is possible to detect the presence of Alzheimer's disease using these measures and in an automated way. These measures also show that shape information is influenced by the vessels' branching structure, as known to be consistent with Alzheimer's disease evolution.
机译:我们描述了如何使用图像分析来检测阿尔茨海默氏病的存在。数据是从患有和未患有阿尔茨海默氏病的受试者中收集的脑组织图像。该分析着重于已知受淀粉样β蛋白影响的血管的形状和结构,β淀粉样蛋白的引流受阿尔茨海默氏病的影响。通过一种测量血管分支结构影响的新方法对结构进行了分析。结合使用傅立叶描述符得出的边界描述来分析其密度和曲折度。这些措施形成了从脑组织图像派生的特征向量,并且判别能力表明,可以使用这些措施并以自动化方式检测阿尔茨海默氏病的存在。这些措施还表明,形状信息受血管分支结构的影响,众所周知,这与阿尔茨海默氏病的进展一致。

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