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| Presentation | 2022-12-05 15:10 Application of Adversarial Training in Detection of Calcification Regions from Dental Panoramic Radiographs Sei Takano, Mitsuji Muneyasu, Soh Yoshida, Akira Asano (Kansai Univ.), Keiichi Uchida (Matsumoto Dental Univ. Hospital)  SIS2022-28 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Calcification regions that are a sign of vascular diseases may be observed on dental panoramic radiographs. The finding of calcification regions can be used to prevent the sudden onset of vascular disorders by encouraging dental patients to seek medical attention. For this purpose, automatic detection methods based on semantic segmentation have been proposed, but the amount of data used is small, and the identification accuracy is insufficient. This paper proposes a method to solve this problem by applying adversarial training to TransFuse network based on Transformer and convolutional neural network (CNN). Adversarial Features are introduced as adversarial training to the semantic segmentation problem. The proposed method is expected to improve the segmentation accuracy even with a small dataset. The effectiveness of the proposed method was confirmed by applying it to actual data. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | dental panoramic radiograph / vascular disease / deep learning / semantic segmentation / regularization / adversarial examples / / | |
| Reference Info. | IEICE Tech. Rep., vol. 122, no. 293, SIS2022-28, pp. 26-31, Dec. 2022. | |
| Paper # | SIS2022-28 | |
| Date of Issue | 2022-11-28 (SIS) | |
| ISSN | 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 | SIS2022-28 |
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| Conference Information | |
| Committee | SIS |
| Conference Date | 2022-12-05 - 2022-12-06 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | SIS |
| Conference Code | 2022-12-SIS |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Application of Adversarial Training in Detection of Calcification Regions from Dental Panoramic Radiographs |
| Sub Title (in English) | |
| Keyword(1) | dental panoramic radiograph |
| Keyword(2) | vascular disease |
| Keyword(3) | deep learning |
| Keyword(4) | semantic segmentation |
| Keyword(5) | regularization |
| Keyword(6) | adversarial examples |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Sei Takano |
| 1st Author's Affiliation | Kansai University (Kansai Univ.) |
| 2nd Author's Name | Mitsuji Muneyasu |
| 2nd Author's Affiliation | Kansai University (Kansai Univ.) |
| 3rd Author's Name | Soh Yoshida |
| 3rd Author's Affiliation | Kansai University (Kansai Univ.) |
| 4th Author's Name | Akira Asano |
| 4th Author's Affiliation | Kansai University (Kansai Univ.) |
| 5th Author's Name | Keiichi Uchida |
| 5th Author's Affiliation | Matsumoto Dental University Hospital, (Matsumoto Dental Univ. Hospital) |
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| Speaker | Author-1 |
| Date Time | 2022-12-05 15:10:00 |
| Presentation Time | 20 minutes |
| Registration for | SIS |
| Paper # | SIS2022-28 |
| Volume (vol) | vol.122 |
| Number (no) | no.293 |
| Page | pp.26-31 |
| #Pages | 6 |
| Date of Issue | 2022-11-28 (SIS) |
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