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Paper Abstract and Keywords
Presentation 2026-02-20 15:30
Improved Mammogram Registration Using Pectoralis Major Muscle Segmentation
Masahiro Shirahata (Muroran Institute Univ.), Chiharu Kai, Satoshi Kasai (Fujita Health Univ.), Satoshi Kondo (Muroran Institute Univ.) ITS2025-78 IE2025-93
Abstract (in Japanese) (See Japanese page) 
(in English) Mammograms, X-ray images specifically for the breast, are used to detect abnormalities for the purpose of early breast cancer detection. It is also known that diagnostic accuracy improves through comparative reading, which involves comparing images from both breasts or comparing past and current images. Comparative reading can reduce the burden on radiologists by using difference processing to highlight differences between breasts and changes over time. However, breast tissue is soft and easily deformed, and shape variations can be significant depending on imaging conditions, making precise alignment essential for high-accuracy difference processing. Previous studies confirmed improved accuracy by pre-masking the pectoralis major muscle region visible in MLO images during evaluation before performing alignment. However, con-sideration of the pectoralis major muscle region during training was insufficient. Therefore, this paper investigates a method where mammograms are segmented during training to detect the pectoralis major muscle region, and this region is ignored during loss function calculation and deformation field estimation. This approach aims to improve the registration accuracy of the breast tissue and skin line by ignoring the pectoralis major region, which may affect registration but is not diagnostically necessary. Experiments were conducted on a total of 16 groups classified into four groups based on breast tissue content and breast thickness (compression thickness). Registration accuracy was confirmed through both subjective evaluation based on images and objective evaluation using numerical metrics.
Keyword (in Japanese) (See Japanese page) 
(in English) mammogram / Voxelmorph / U-Net / Alignment / Segmentation / / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 356, IE2025-93, pp. 222-227, Feb. 2026.
Paper # IE2025-93 
Date of Issue 2026-02-12 (ITS, IE) 
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 ITS2025-78 IE2025-93

Conference Information
Committee IE ITS ITE-MMS ITE-ME ITE-AIT ITE-SIP  
Conference Date 2026-02-19 - 2026-02-20 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To IE 
Conference Code 2026-02-IE-ITS-MMS-ME-AIT-SIP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Improved Mammogram Registration Using Pectoralis Major Muscle Segmentation 
Sub Title (in English)  
Keyword(1) mammogram  
Keyword(2) Voxelmorph  
Keyword(3) U-Net  
Keyword(4) Alignment  
Keyword(5) Segmentation  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Masahiro Shirahata  
1st Author's Affiliation Muroran Institute of Technology (Muroran Institute Univ.)
2nd Author's Name Chiharu Kai  
2nd Author's Affiliation Fujita Health University (Fujita Health Univ.)
3rd Author's Name Satoshi Kasai  
3rd Author's Affiliation Fujita Health University (Fujita Health Univ.)
4th Author's Name Satoshi Kondo  
4th Author's Affiliation Muroran Institute of Technology (Muroran Institute Univ.)
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Speaker Author-1 
Date Time 2026-02-20 15:30:00 
Presentation Time 15 minutes 
Registration for IE 
Paper # ITS2025-78, IE2025-93 
Volume (vol) vol.125 
Number (no) no.355(ITS), no.356(IE) 
Page pp.222-227 
#Pages 6 
Date of Issue 2026-02-12 (ITS, IE) 

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