Age estimation from brain MRI images using deep learning

Tzu Wei Huang; Hwann Tzong Chen; Ryuichi Fujimoto; Koichi Ito; Kai Wu; Kazunori Sato; Yasuyuki Taki; Hiroshi Fukuda; Takafumi Aoki

doi:10.1109/ISBI.2017.7950650

Age estimation from brain MRI images using deep learning

Tzu Wei Huang, Hwann Tzong Chen, Ryuichi Fujimoto, Koichi Ito, Kai Wu, Kazunori Sato, Yasuyuki Taki, Hiroshi Fukuda, Takafumi Aoki

研究成果: 書籍の章/レポート/Proceedings › 会議への寄与 › 査読

58 被引用数 (Scopus)

抄録

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.

本文言語	英語
ホスト出版物のタイトル	2017 IEEE 14th International Symposium on Biomedical Imaging, ISBI 2017
出版社	IEEE Computer Society
ページ	849-852
ページ数	4
ISBN（電子版）	9781509011711
DOI	https://doi.org/10.1109/ISBI.2017.7950650
出版ステータス	出版済み - 2017 6月 15
イベント	14th IEEE International Symposium on Biomedical Imaging, ISBI 2017 - Melbourne, オーストラリア継続期間: 2017 4月 18 → 2017 4月 21

出版物シリーズ

名前	Proceedings - International Symposium on Biomedical Imaging
ISSN（印刷版）	1945-7928
ISSN（電子版）	1945-8452

会議

会議	14th IEEE International Symposium on Biomedical Imaging, ISBI 2017
国/地域	オーストラリア
City	Melbourne
Period	17/4/18 → 17/4/21

UN SDG

この成果は、次の持続可能な開発目標に貢献しています

文献へのアクセス

10.1109/ISBI.2017.7950650

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引用スタイル

Huang, T. W., Chen, H. T., Fujimoto, R., Ito, K., Wu, K., Sato, K., Taki, Y., Fukuda, H., & Aoki, T. (2017). Age estimation from brain MRI images using deep learning. In 2017 IEEE 14th International Symposium on Biomedical Imaging, ISBI 2017 (pp. 849-852). 記事 7950650 (Proceedings - International Symposium on Biomedical Imaging). IEEE Computer Society. https://doi.org/10.1109/ISBI.2017.7950650

@inproceedings{babcc9af2e3e4aedb19bd8a0ac9661e3,

title = "Age estimation from brain MRI images using deep learning",

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.",

keywords = "Age estimation, Brain-aging, Deep learning, MRI, T1-weighted image",

author = "Huang, {Tzu Wei} and Chen, {Hwann Tzong} and Ryuichi Fujimoto and Koichi Ito and Kai Wu and Kazunori Sato and Yasuyuki Taki and Hiroshi Fukuda and Takafumi Aoki",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 14th IEEE International Symposium on Biomedical Imaging, ISBI 2017 ; Conference date: 18-04-2017 Through 21-04-2017",

year = "2017",

month = jun,

day = "15",

doi = "10.1109/ISBI.2017.7950650",

language = "English",

series = "Proceedings - International Symposium on Biomedical Imaging",

publisher = "IEEE Computer Society",

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Huang, TW, Chen, HT, Fujimoto, R, Ito, K, Wu, K, Sato, K, Taki, Y, Fukuda, H & Aoki, T 2017, Age estimation from brain MRI images using deep learning. in 2017 IEEE 14th International Symposium on Biomedical Imaging, ISBI 2017., 7950650, Proceedings - International Symposium on Biomedical Imaging, IEEE Computer Society, pp. 849-852, 14th IEEE International Symposium on Biomedical Imaging, ISBI 2017, Melbourne, オーストラリア, 17/4/18. https://doi.org/10.1109/ISBI.2017.7950650

Age estimation from brain MRI images using deep learning. / Huang, Tzu Wei; Chen, Hwann Tzong; Fujimoto, Ryuichi その他.
2017 IEEE 14th International Symposium on Biomedical Imaging, ISBI 2017. IEEE Computer Society, 2017. p. 849-852 7950650 (Proceedings - International Symposium on Biomedical Imaging).

研究成果: 書籍の章/レポート/Proceedings › 会議への寄与 › 査読

TY - GEN

T1 - Age estimation from brain MRI images using deep learning

AU - Huang, Tzu Wei

AU - Chen, Hwann Tzong

AU - Fujimoto, Ryuichi

AU - Ito, Koichi

AU - Wu, Kai

AU - Sato, Kazunori

AU - Taki, Yasuyuki

AU - Fukuda, Hiroshi

AU - Aoki, Takafumi

PY - 2017/6/15

Y1 - 2017/6/15

N2 - 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.

AB - 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.

KW - Age estimation

KW - Brain-aging

KW - Deep learning

KW - MRI

KW - T1-weighted image

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M3 - Conference contribution

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T3 - Proceedings - International Symposium on Biomedical Imaging

SP - 849

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BT - 2017 IEEE 14th International Symposium on Biomedical Imaging, ISBI 2017

PB - IEEE Computer Society

T2 - 14th IEEE International Symposium on Biomedical Imaging, ISBI 2017

Y2 - 18 April 2017 through 21 April 2017

ER -

Age estimation from brain MRI images using deep learning

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