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| Presentation | 2016-07-25 15:15 A Study of an Efficient Method of Selecting Effective Brain Local Features for Age Estimation Ryuichi Fujimoto, Koichi Ito (Tohoku Univ.), Kai Wu (South China Univ.), Kazunori Sato, Yasuyuki Taki (Tohoku Univ.), Hiroshi Fukuda (Tohoku Medical And Pharmaceutical Univ.), Takafumi Aoki (Tohoku Univ.)  MI2016-38 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Estimating the age of a subject by evaluating brain morphological changes leads diagnostic support or early detection of disease like Alzheimer’s Disease. In the age estimation method using local features extracted from T1-weighted MRI images, the accuracy of the age estimation increases when only using effective local features. By using local features defined by finely divided atlas, estimating accuracy would increase. However, it takes too much computation time because of the increasing of the number of local regions. To solve this problem, this paper proposes an efficient method of selecting effective brain local features for age estimation, and evaluate performance of the proposed method. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | MRI / T1-weighted image / age estimation / brain aging / local features / machine learning / relevance vector machine / | |
| Reference Info. | IEICE Tech. Rep., vol. 116, no. 160, MI2016-38, pp. 13-18, July 2016. | |
| Paper # | MI2016-38 | |
| Date of Issue | 2016-07-18 (MI) | |
| ISSN | Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 | |
| Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) | |
| Download PDF | MI2016-38 |
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| Conference Information | |
| Committee | MI |
| Conference Date | 2016-07-25 - 2016-07-26 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Tomakomai Civic Hall |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Medical Imaging, etc. |
| Paper Information | |
| Registration To | MI |
| Conference Code | 2016-07-MI |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A Study of an Efficient Method of Selecting Effective Brain Local Features for Age Estimation |
| 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 |
| Keyword(8) | |
| 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.) |
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| Speaker | Author-1 |
| Date Time | 2016-07-25 15:15:00 |
| Presentation Time | 30 minutes |
| Registration for | MI |
| Paper # | MI2016-38 |
| Volume (vol) | vol.116 |
| Number (no) | no.160 |
| Page | pp.13-18 |
| #Pages | 6 |
| Date of Issue | 2016-07-18 (MI) |
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