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SUPPORT METHOD AND AUTOMATED SYSTEM FOR PREDICTING ALZHEIMER DISEASE, AND TRAINING METHOD OF THE SYSTEM

机译:预测老年痴呆症的支持方法和自动化系统,以及系统的训练方法

摘要

PROBLEM TO BE SOLVED: To provide a support method and an automated system for predicting the course of an Alzheimer disease of a patient contracting mild cognitive impairment or MCI and diagnosing the Alzheimer disease.;SOLUTION: The present invention relates to identifying a discrimination area of a brain and finely adjusting a support method on the basis of an up-to-date known case using the area. Further, the present invention relates to a method for training a system. Imaging data (PET or MPET) expressing brain activity in a plurality of spatial areas (voxel) is used. Thus, the method includes a process of standardizing image data, and analysis of a value of the brain activity recognized in selection of the voxel forming at least one predetermined discrimination area to be defined by a coordinate in a spatial reference system. Furthermore, the method may include a combination of an imaging result and one or more results of cognition tests.;COPYRIGHT: (C)2014,JPO&INPIT
机译:解决的问题:提供一种预测患有轻度认知障碍或MCI的患者的阿尔茨海默氏病病程并诊断该阿尔茨海默氏病的支持方法和自动化系统。大脑,并根据使用该区域的最新已知病例微调支持方法。此外,本发明涉及用于训练系统的方法。使用在多个空间区域(体素)中表达大脑活动的成像数据(PET或MPET)。因此,该方法包括以下步骤:对图像数据进行标准化;以及对在选择形成至少一个预定辨别区域的体素时识别出的大脑活动的值进行分析,该预定辨别区域将由空间参考系统中的坐标来定义。此外,该方法可以包括成像结果和认知测试的一个或多个结果的组合。版权所有:(C)2014,JPO&INPIT

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