基于PSO和决策树方法的脑图像阿尔茨海默病检测

M. Sweety, G. Jiji
{"title":"基于PSO和决策树方法的脑图像阿尔茨海默病检测","authors":"M. Sweety, G. Jiji","doi":"10.1109/ICACCCT.2014.7019310","DOIUrl":null,"url":null,"abstract":"Alzheimer's disease (AD) is a disease that attacks the brain which worsens as it progresses and it eventually lead to the death. This paper is based on the proposed technique Particle swarm optimization (PSO) for feature reduction and Decision Tree Classifier for classification. Earlier detection of AD is carried out in 3 phases. In the first phase, features such as eigen vectors, eigen brain, mean, variance, skewness, kurtosis, standard deviation, area, perimeter, eccentricity are extracted from MRI Images. In the second phase, feature reduction is carried out by Particle swarm optimization(PSO) and in third phase, Decision Tree Classifier is used to detect whether the brain image is affected by the Alzheimer disease or not. The proposed work is also compared with earlier works.","PeriodicalId":239918,"journal":{"name":"2014 IEEE International Conference on Advanced Communications, Control and Computing Technologies","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"Detection of Alzheimer disease in brain images using PSO and Decision Tree Approach\",\"authors\":\"M. Sweety, G. Jiji\",\"doi\":\"10.1109/ICACCCT.2014.7019310\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Alzheimer's disease (AD) is a disease that attacks the brain which worsens as it progresses and it eventually lead to the death. This paper is based on the proposed technique Particle swarm optimization (PSO) for feature reduction and Decision Tree Classifier for classification. Earlier detection of AD is carried out in 3 phases. In the first phase, features such as eigen vectors, eigen brain, mean, variance, skewness, kurtosis, standard deviation, area, perimeter, eccentricity are extracted from MRI Images. In the second phase, feature reduction is carried out by Particle swarm optimization(PSO) and in third phase, Decision Tree Classifier is used to detect whether the brain image is affected by the Alzheimer disease or not. The proposed work is also compared with earlier works.\",\"PeriodicalId\":239918,\"journal\":{\"name\":\"2014 IEEE International Conference on Advanced Communications, Control and Computing Technologies\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-05-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE International Conference on Advanced Communications, Control and Computing Technologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICACCCT.2014.7019310\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE International Conference on Advanced Communications, Control and Computing Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICACCCT.2014.7019310","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18

摘要

阿尔茨海默病(AD)是一种攻击大脑的疾病,随着病情的发展,病情会恶化,最终导致死亡。本文采用粒子群算法进行特征约简,决策树分类器进行分类。AD的早期检测分三个阶段进行。首先,从MRI图像中提取特征向量、特征脑、均值、方差、偏度、峰度、标准差、面积、周长、偏心率等特征。第二阶段采用粒子群算法(PSO)进行特征约简,第三阶段采用决策树分类器检测脑图像是否受阿尔茨海默病影响。本文还与前人的研究成果进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Detection of Alzheimer disease in brain images using PSO and Decision Tree Approach
Alzheimer's disease (AD) is a disease that attacks the brain which worsens as it progresses and it eventually lead to the death. This paper is based on the proposed technique Particle swarm optimization (PSO) for feature reduction and Decision Tree Classifier for classification. Earlier detection of AD is carried out in 3 phases. In the first phase, features such as eigen vectors, eigen brain, mean, variance, skewness, kurtosis, standard deviation, area, perimeter, eccentricity are extracted from MRI Images. In the second phase, feature reduction is carried out by Particle swarm optimization(PSO) and in third phase, Decision Tree Classifier is used to detect whether the brain image is affected by the Alzheimer disease or not. The proposed work is also compared with earlier works.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A hybrid approach to synchronization in real time multiprocessor systems An effective tree metrics graph cut algorithm for MR brain image segmentation and tumor Identification Performance tradeoffs between diversity schemes in wireless systems Fixed point pipelined architecture for QR decomposition Reliability of different levels of cascaded H-Bridge inverter: An investigation and comparison
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1