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Paper Abstract and Keywords
Presentation 2024-03-14 14:50
Improvement of Detection Accuracy for Detection of Calcification Regions in Dental Panoramic Radiographs Using LVAT
Naoki Ikeda, Sei Takano, Mitsuji Muneyasu, Soh Yoshida, Akira Asano (Kansai Univ.), Nanae Dewake, Nobuo Yoshinari (Matsumoto Dental Univ.), Keiichi Uchida (Matsumoto Dental Univ. Hospital) SIS2023-50
Abstract (in Japanese) (See Japanese page) 
(in English) Carotid arteries on dental panoramic radiographs may show areas of calcification, a sign of vascular disease. The sudden onset of vascular disease can be prevented by detecting these areas at the dental clinic, and the dentist prompts a visit to a physician. A method based on semantic segmentation has been proposed as an automatic detection method for this purpose. However, because of the small number of available data, the detection accuracy of calcification regions is insufficient. In this paper, we propose a method by applying Latent Space Virtual Adversarial Training (LVAT), a type of adversarial training. We also describe a method to improve the pre-training of Variational Auto Encoder (VAE), which is essential in LVAT, using healthy subjects' data. This method is expected to improve the detection accuracy even with a limited number of data. The effectiveness of the proposed method is demonstrated by applying it to actual data.
Keyword (in Japanese) (See Japanese page) 
(in English) dental panoramic radiograph / vascular disease / semantic segmentation / regularization / adversarial example / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 440, SIS2023-50, pp. 27-32, March 2024.
Paper # SIS2023-50 
Date of Issue 2024-03-07 (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 SIS2023-50

Conference Information
Committee SIS  
Conference Date 2024-03-14 - 2024-03-15 
Place (in Japanese) (See Japanese page) 
Place (in English) Kanagawa Institute of Technology 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Soft computing, etc. 
Paper Information
Registration To SIS 
Conference Code 2024-03-SIS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Improvement of Detection Accuracy for Detection of Calcification Regions in Dental Panoramic Radiographs Using LVAT 
Sub Title (in English)  
Keyword(1) dental panoramic radiograph  
Keyword(2) vascular disease  
Keyword(3) semantic segmentation  
Keyword(4) regularization  
Keyword(5) adversarial example  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Naoki Ikeda  
1st Author's Affiliation Kansai University (Kansai Univ.)
2nd Author's Name Sei Takano  
2nd Author's Affiliation Kansai University (Kansai Univ.)
3rd Author's Name Mitsuji Muneyasu  
3rd Author's Affiliation Kansai University (Kansai Univ.)
4th Author's Name Soh Yoshida  
4th Author's Affiliation Kansai University (Kansai Univ.)
5th Author's Name Akira Asano  
5th Author's Affiliation Kansai University (Kansai Univ.)
6th Author's Name Nanae Dewake  
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 Keiichi Uchida  
8th Author's Affiliation Matsumoto Dental University Hospital (Matsumoto Dental Univ. Hospital)
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Speaker Author-1 
Date Time 2024-03-14 14:50:00 
Presentation Time 20 minutes 
Registration for SIS 
Paper # SIS2023-50 
Volume (vol) vol.123 
Number (no) no.440 
Page pp.27-32 
#Pages 6 
Date of Issue 2024-03-07 (SIS) 

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