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":"18 1","pages":"849-852"},"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.