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| Presentation | 2019-12-12 13:50 Improvement of Detection Accuracy of Calcified Area from Dental Panoramic Radiograph Using Deep Learning Yasuhiro Yamazaki, Mitsuji Muneyasu, Soh Yoshida, Akira Asano (Kansai Univ.), Keiichi Uchida, Yasuaki Ishioka, Nobuo Yoshinari, Akira Taguchi (Matsumoto Dental Univ.)  SIS2019-24 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In dental panoramic radiographs, calcification regions, which may be a sign of vascular disease, can be found. It is possible to prevent the sudden onset of vascular disease by judging the presence of calcification by dentists and promoting medical care by physicians. Several methods have been proposed for automatic judging the presence of the calcification regions. However, the identification accuracy is insufficient because of the ambiguity of the features of the calcification regions. Therefore, we propose a method of applying deep learning to the estimation of the position of the calcification regions. The experimental results show that the proposed method can improve the detection accuracy. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | calcification region / dental panoramic radiograph / automatic detection / vascular disease / deep learning / neural network / / | |
| Reference Info. | IEICE Tech. Rep., vol. 119, no. 335, SIS2019-24, pp. 5-10, Dec. 2019. | |
| Paper # | SIS2019-24 | |
| Date of Issue | 2019-12-05 (SIS) | |
| 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 | SIS2019-24 |
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| Conference Information | |
| Committee | SIS |
| Conference Date | 2019-12-12 - 2019-12-13 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Okayama University of Science |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Smart Personal Systems, etc. |
| Paper Information | |
| Registration To | SIS |
| Conference Code | 2019-12-SIS |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Improvement of Detection Accuracy of Calcified Area from Dental Panoramic Radiograph Using Deep Learning |
| Sub Title (in English) | |
| Keyword(1) | calcification region |
| Keyword(2) | dental panoramic radiograph |
| Keyword(3) | automatic detection |
| Keyword(4) | vascular disease |
| Keyword(5) | deep learning |
| Keyword(6) | neural network |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Yasuhiro Yamazaki |
| 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 (Matsumoto Dental Univ.) |
| 6th Author's Name | Yasuaki Ishioka |
| 6th Author's Affiliation | Matsumoto Dental University (Matsumoto Dental Univ.) |
| 7th Author's Name | Nobuo Yoshinari |
| 7th Author's Affiliation | Matsumoto Dental University (Matsumoto Dental Univ.) |
| 8th Author's Name | Akira Taguchi |
| 8th Author's Affiliation | Matsumoto Dental University (Matsumoto Dental Univ.) |
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| Speaker | Author-1 |
| Date Time | 2019-12-12 13:50:00 |
| Presentation Time | 20 minutes |
| Registration for | SIS |
| Paper # | SIS2019-24 |
| Volume (vol) | vol.119 |
| Number (no) | no.335 |
| Page | pp.5-10 |
| #Pages | 6 |
| Date of Issue | 2019-12-05 (SIS) |
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