Age Estimation Using Effective Brain Local Features from T1-Weighted Images

被引：0

作者：

Fujimoto, Ryuichi ^{[1
]}

Kondo, Chihiro ^{[1
]}

Ito, Koichi ^{[1
]}

Wu, Kai ^{[2
]}

Sato, Kazunori ^{[3
]}

Taki, Yasuyuki ^{[3
]}

Fukuda, Hiroshi ^{[4
]}

Aoki, Takafumi ^{[1
]}

机构：

[1] Tohoku Univ, Grad Sch Informat Scienves, Sendai, Miyagi, Japan

[2] South China Univ Technol, Guangzhou, Guangdong, Peoples R China

[3] Tohoku Univ, Inst Dev Aging & Canc, Sendai, Miyagi, Japan

[4] Tohoku Pharmaceut Univ, Sendai, Miyagi, Japan

来源：

2016 38TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC) | 2016年

关键词：

PARCELLATION;

D O I：

暂无

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

This paper proposes a simple method of selecting effective brain local features for age estimation from T1-weighted MR images. We also employ the high-resolution AAL atlas, which is defined by 1,024 local regions, to improve the accuracy of age estimation. We evaluate performance of the proposed method using 1,099 T1-weighted images from a large-scale brain MR image database of healthy Japanese, and demonstrate that the proposed method exhibits efficient performance of age estimation compared with conventional methods.

引用

页码：5941 / 5944

页数：4

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