首页> 外国专利> METHOD FOR DETECTION OF ALZHEIMER'S DISEASE SYSTEM FOR DETECTION OF ALZHEIMER'S DISEASE AND COMPUTER-READABLE MEDIUM STORING PROGRAM FOR METHOD THEREOF

METHOD FOR DETECTION OF ALZHEIMER'S DISEASE SYSTEM FOR DETECTION OF ALZHEIMER'S DISEASE AND COMPUTER-READABLE MEDIUM STORING PROGRAM FOR METHOD THEREOF

机译:检测阿兹海默病的系统的方法检测阿兹海默病的方法及其计算机可读介质存储程序

摘要

The present invention relates to a method for detection of Alzheimer′s disease, a system for detection of Alzheimer′s disease, and a computer-readable medium storing a program for performing the method for detection of Alzheimer′s disease. The method for detection of Alzheimer′s disease according to an embodiment of the present invention comprises: a preprocessing step of extracting non-white matter data by analyzing magnetic resonance imaging (MRI) data and positron emission tomography (PET) image data; a step of updating a weight by calculating non-white matter data using a convolutional autoencoder (CAE); a step of extracting feature data by applying the updated weight to a kernel of a hidden layer of a convolutional neural network (CNN); and a step of calculating the probability of Alzheimer′s disease stage using the extracted feature data. According to the present invention, the stages of Alzheimer′s disease can be classified and judged more clearly.
机译:本发明涉及一种用于检测阿尔茨海默氏病的方法,一种用于检测阿尔茨海默氏病的系统以及一种计算机可读介质,该计算机可读介质存储了用于执行用于检测阿尔茨海默氏病的方法的程序。根据本发明实施例的用于检测阿尔茨海默氏病的方法包括:预处理步骤,其通过分析磁共振成像(MRI)数据和正电子发射断层扫描(PET)图像数据来提取非白质数据;通过使用卷积自动编码器(CAE)计算非白质数据来更新权重的步骤;通过将更新的权重应用于卷积神经网络(CNN)的隐藏层的内核来提取特征数据的步骤;以及使用所提取的特征数据来计算阿尔茨海默氏病阶段的可能性的步骤。根据本发明,可以对阿尔茨海默氏病的阶段进行分类和更清楚地判断。

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