{"title":"基于GDA的阿尔茨海默病早期检测分类算法","authors":"K. P. Thejaswini, B. A. Sujatha Kumari","doi":"10.1109/ICCS45141.2019.9065526","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":433980,"journal":{"name":"2019 International Conference on Intelligent Computing and Control Systems (ICCS)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"GDA Based Classification Algorithm for Early Detection of Alzheimer’s disease\",\"authors\":\"K. P. Thejaswini, B. A. Sujatha Kumari\",\"doi\":\"10.1109/ICCS45141.2019.9065526\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":433980,\"journal\":{\"name\":\"2019 International Conference on Intelligent Computing and Control Systems (ICCS)\",\"volume\":\"77 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Intelligent Computing and Control Systems (ICCS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCS45141.2019.9065526\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Intelligent Computing and Control Systems (ICCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCS45141.2019.9065526","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.