Age estimation from brain MRI images using deep learning

Tzu-Wei Huang, Hwann-Tzong Chen, Ryuichi Fujimoto, Koichi Ito, Kai Wu, Kazunori Sato, Y. Taki, H. Fukuda, T. Aoki
{"title":"Age estimation from brain MRI images using deep learning","authors":"Tzu-Wei Huang, Hwann-Tzong Chen, Ryuichi Fujimoto, Koichi Ito, Kai Wu, Kazunori Sato, Y. Taki, H. Fukuda, T. Aoki","doi":"10.1109/ISBI.2017.7950650","DOIUrl":null,"url":null,"abstract":"Estimating human age from brain MR images is useful for early detection of Alzheimer's disease. In this paper we propose a fast and accurate method based on deep learning to predict subject's age. Compared with previous methods, our algorithm achieves comparable accuracy using fewer input images. With our GPU version program, the time needed to make a prediction is 20 ms. We evaluate our methods using mean absolute error (MAE) and our method is able to predict subject's age with MAE of 4.0 years.","PeriodicalId":6547,"journal":{"name":"2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"48","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISBI.2017.7950650","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 48

Abstract

Estimating human age from brain MR images is useful for early detection of Alzheimer's disease. In this paper we propose a fast and accurate method based on deep learning to predict subject's age. Compared with previous methods, our algorithm achieves comparable accuracy using fewer input images. With our GPU version program, the time needed to make a prediction is 20 ms. We evaluate our methods using mean absolute error (MAE) and our method is able to predict subject's age with MAE of 4.0 years.
利用深度学习从脑MRI图像中估计年龄
从脑磁共振图像估计人的年龄对阿尔茨海默病的早期检测是有用的。本文提出了一种基于深度学习的快速准确的受试者年龄预测方法。与以前的方法相比,我们的算法使用更少的输入图像达到了相当的精度。使用我们的GPU版本程序,进行预测所需的时间是20毫秒。我们使用平均绝对误差(MAE)来评估我们的方法,我们的方法能够预测受试者的年龄,MAE为4.0岁。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信