基于GDA的阿尔茨海默病早期检测分类算法

K. P. Thejaswini, B. A. Sujatha Kumari
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引用次数: 0

摘要

患有阿尔茨海默病的人不能正常说话。因为中枢神经系统坏了,他们就不能正常工作了。他们需要依靠家庭成员来完成他们的工作。许多研究预测,到2050年,全世界将有大约1.15亿人患有阿尔茨海默病(AD)。早期发现阿尔茨海默病至关重要,因此可以采取预防措施。利用人脑核磁共振成像(MRI)信息来检测AD。海马体是大脑的重要组成部分之一。人的正常行为取决于海马体的功能。海马体专家的手工分割需要几个小时。阿尔茨海默病检测与分类系统包括MRI预处理、分割、高斯判别分析(GDA)特征提取和支持向量机(SVM)分类四个阶段。利用ADNI数据集对该策略进行了评估。所提出的技术的结果表明这个人是否有AD。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GDA Based Classification Algorithm for Early Detection of Alzheimer’s disease
People suffering from Alzheimer’s disease aren’t able to speak properly. Since central nervous system get broken they can't do their work properly. they need to depend on their members of the family to do their work. The many studies projected that more or less one hundred fifteen million individuals are going to be affected from Alzheimer disease (AD) worldwide by the year 2050. Early detection of AD is vital so preventative measures may be taken place. The human brain magnetic resonance imaging (MRI) information are used to detection of AD. one among the vital part of the brain is Hippocampus. the normal behavior of persons is depends on the functionality of Hippocampus. Manual Segmentation by a specialist on the Hippocampus takes several hours. The Alzheimer detection and classification systems include four stages, namely, MRI preprocessing, Segmentation, Feature extraction by gaussian Discriminant Analysis (GDA), and Classification by Support Vector Machine (SVM). the strategy is evaluated by exploitation an ADNI dataset. The results of the proposed technique indicate the person is littered with AD or not.
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