Presentation 2017-05-26
An Age Estimation Method Using Brain Local Features of Brain MRI Images and Its Performance Evaluation
Ryuichi Fujimoto, Koichi Ito, Kai Wu, Kazunori Sato, Yasuyuki Taki, Hiroshi Fukuda, Takafumi Aoki,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) It is known that brain tissues have age-related morphological changes through a set of statistical analysisusing large-scale brain MRI image databases. This fact allows us to estimate the age of a subject from brainMRI images by evaluating brain morphological changes with healthy aging. The age estimated from morphological changes of a human brain can be used for diagnostic support and early identification of brain disorders such as Alzheimer's Disease. This paper proposes an age estimation method using local features extracted from T1-weighted MRI images. Local features are defined by regional volume calculated from 1,024 local regions of GM, WM and CSF. We also add cortical thickness parcellated by Destrieux atlas tobrain local features in order to improve the accuracy ofage estimation. We evaluate performance of the proposed method using a large-scale dataset of healty Japanese.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) MRI / T1-weighted image / age estimation / brain aging / local features / machine learning / relevance vector machine
Paper # SIP2017-13,IE2017-13,PRMU2017-13,MI2017-13
Date of Issue 2017-05-18 (SIP, IE, PRMU, MI)

Conference Information
Committee PRMU / IE / MI / SIP
Conference Date 2017/5/25(2days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Eisaku Maeda(NTT) / Seishi Takamura(NTT) / Yoshitaka Masutani(Hiroshima City Univ.) / Makoto Nakashizuka(Chiba Inst. of Tech.)
Vice Chair Seiichi Uchida(Kyushu Univ.) / Hironobu Fujiyoshi(Chubu Univ.) / Takayuki Hamamoto(Tokyo Univ. of Science) / Atsuro Ichigaya(NHK) / Yoshiki Kawata(Tokushima Univ.) / Yuichi Kimura(Kinki Univ.) / Masahiro Okuda(Univ. of Kitakyushu) / Shogo Muramatsu(Niigata Univ.)
Secretary Seiichi Uchida(Kyoto Univ.) / Hironobu Fujiyoshi(NTT) / Takayuki Hamamoto(NTT) / Atsuro Ichigaya(Chiba Inst. of Tech.) / Yoshiki Kawata(Aichi Inst. of Tech.) / Yuichi Kimura(Nagoya Inst. of Tech.) / Masahiro Okuda(Ritsumeikan Univ.) / Shogo Muramatsu(Chiba Inst. of Tech.)
Assistant Masaki Oonishi(AIST) / Takuya Funatomi(NAIST) / Kei Kawamura(KDDI R&D Labs.) / Keita Takahashi(Nagoya Univ.) / Ryo Haraguchi(Univ. of Hyogo) / Yasushi Hirano(Yamaguchi Univ.) / Osamu Watanabe(Takushoku Univ.)

Paper Information
Registration To Technical Committee on Pattern Recognition and Media Understanding / Technical Committee on Image Engineering / Technical Committee on Medical Imaging / Technical Committee on Signal Processing
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) An Age Estimation Method Using Brain Local Features of Brain MRI Images and Its Performance Evaluation
Sub Title (in English)
Keyword(1) MRI
Keyword(2) T1-weighted image
Keyword(3) age estimation
Keyword(4) brain aging
Keyword(5) local features
Keyword(6) machine learning
Keyword(7) relevance vector machine
1st Author's Name Ryuichi Fujimoto
1st Author's Affiliation Tohoku University(Tohoku Univ.)
2nd Author's Name Koichi Ito
2nd Author's Affiliation Tohoku University(Tohoku Univ.)
3rd Author's Name Kai Wu
3rd Author's Affiliation South China University of Technology(South China Univ.)
4th Author's Name Kazunori Sato
4th Author's Affiliation Tohoku University(Tohoku Univ.)
5th Author's Name Yasuyuki Taki
5th Author's Affiliation Tohoku University(Tohoku Univ.)
6th Author's Name Hiroshi Fukuda
6th Author's Affiliation Tohoku Medical and Pharmaceutical University(Tohoku Medical and Pharmaceutical Univ.)
7th Author's Name Takafumi Aoki
7th Author's Affiliation Tohoku University(Tohoku Univ.)
Date 2017-05-26
Paper # SIP2017-13,IE2017-13,PRMU2017-13,MI2017-13
Volume (vol) vol.117
Number (no) SIP-47,IE-48,PRMU-49,MI-50
Page pp.pp.67-70(SIP), pp.67-70(IE), pp.67-70(PRMU), pp.67-70(MI),
#Pages 4
Date of Issue 2017-05-18 (SIP, IE, PRMU, MI)