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| Presentation | 2020-03-06 11:10 Investigation of diagnostic support system for portable chest X-ray images by two-step classification using ensemble learning Takahiro Dozono, Yuichiro Yoshimura, Kumiko Arai, Takaaki Nakada, Shigeto Oda, Toshiya Nakaguchi (Chiba Univ)  IMQ2019-33 IE2019-115 MVE2019-54 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Portable radiographs are used to monitor critically ill patients in intensive care units who have difficulty moving. However, since it is a photographing in various positions such as sitting position, the interpretation becomes difficult by the difference usual organ condition, and the lowering of the interpretation accuracy becomes a problem. In this study, the adaptation of the deep learning was tried for the purpose of the improvement in diagnostic ability for the chest X-ray portable image. We proposed two-stage classification methods because it is difficult to simultaneously classify atelectasis and pneumonia, pleural effusion, and not emergency. In addition, the accuracy improvement by ensemble learning which combined the multiple models learned in the same input image was examined. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Deep learning / Portable chest x-ray images / Convolutional neural networks / Ensemble learning / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 119, no. 454, IMQ2019-33, pp. 89-92, March 2020. | |
| Paper # | IMQ2019-33 | |
| Date of Issue | 2020-02-27 (IMQ, IE, MVE) | |
| 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 | IMQ2019-33 IE2019-115 MVE2019-54 |
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| Conference Information | |
| Committee | IE IMQ MVE CQ |
| Conference Date | 2020-03-05 - 2020-03-06 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Kyushu Institute of Technology |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | IMQ |
| Conference Code | 2020-03-IE-IMQ-MVE-CQ |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Investigation of diagnostic support system for portable chest X-ray images by two-step classification using ensemble learning |
| Sub Title (in English) | |
| Keyword(1) | Deep learning |
| Keyword(2) | Portable chest x-ray images |
| Keyword(3) | Convolutional neural networks |
| Keyword(4) | Ensemble learning |
| Keyword(5) | |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Takahiro Dozono |
| 1st Author's Affiliation | Chiba University (Chiba Univ) |
| 2nd Author's Name | Yuichiro Yoshimura |
| 2nd Author's Affiliation | Frontier Medical Engineering Center, Chiba University (Chiba Univ) |
| 3rd Author's Name | Kumiko Arai |
| 3rd Author's Affiliation | Department of Emergency and Critical Care Medicine, Chiba University Graduate School of Medicine (Chiba Univ) |
| 4th Author's Name | Takaaki Nakada |
| 4th Author's Affiliation | Department of Emergency and Critical Care Medicine, Chiba University Graduate School of Medicine (Chiba Univ) |
| 5th Author's Name | Shigeto Oda |
| 5th Author's Affiliation | Department of Emergency and Critical Care Medicine, Chiba University Graduate School of Medicine (Chiba Univ) |
| 6th Author's Name | Toshiya Nakaguchi |
| 6th Author's Affiliation | Frontier Medical Engineering Center, Chiba University (Chiba Univ) |
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| Speaker | Author-1 |
| Date Time | 2020-03-06 11:10:00 |
| Presentation Time | 25 minutes |
| Registration for | IMQ |
| Paper # | IMQ2019-33, IE2019-115, MVE2019-54 |
| Volume (vol) | vol.119 |
| Number (no) | no.454(IMQ), no.456(IE), no.457(MVE) |
| Page | pp.89-92 |
| #Pages | 4 |
| Date of Issue | 2020-02-27 (IMQ, IE, MVE) |
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