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Paper Abstract and Keywords
Presentation 2026-02-20 16:00
Report Generation from Chest X-ray Images Using a Vision-Language Model with Document Structure Awareness
Ayato Ohta (MuroranIT), Chiharu Kai, Satoshi Kasai (FJT), Satoshi Kondo (MuroranIT) ITS2025-80 IE2025-95
Abstract (in Japanese) (See Japanese page) 
(in English) Chest X-ray images play an important role in the early detection and follow-up of many diseases; however, interpreting the large volume of chest X-ray images required for diagnosis places a substantial burden on radiologists. Consequently, automatic generation of radiology reports from chest X-ray images using vision–language models (VLMs) has attracted increasing attention. Despite this, existing VLM-based report generation methods do not sufficiently consider the document structure of radiology reports during model training and evaluation.
In this study, we propose a structure-aware training approach that computes the loss separately for each section of a radiology report, namely Findings and Impression. In addition to evaluating the generated reports as a whole, we also conduct section-wise evaluations to verify the effectiveness of the proposed method. Experimental results show that the proposed approach improves both generation performance and report length for the full report and the Findings section compared with existing methods. In contrast, no improvement is observed for the Impression section, revealing the difficulty of learning sections that appear later in the document structure.
Keyword (in Japanese) (See Japanese page) 
(in English) LLM / VLM / Chest X-ray / report generation / Llama / / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 356, IE2025-95, pp. 233-238, Feb. 2026.
Paper # IE2025-95 
Date of Issue 2026-02-12 (ITS, IE) 
ISSN Online edition: ISSN 2432-6380
Copyright
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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 ITS2025-80 IE2025-95

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) Report Generation from Chest X-ray Images Using a Vision-Language Model with Document Structure Awareness 
Sub Title (in English)  
Keyword(1) LLM  
Keyword(2) VLM  
Keyword(3) Chest X-ray  
Keyword(4) report generation  
Keyword(5) Llama  
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Keyword(8)  
1st Author's Name Ayato Ohta  
1st Author's Affiliation Muroran Institute of Technology (MuroranIT)
2nd Author's Name Chiharu Kai  
2nd Author's Affiliation Fujita Helth University (FJT)
3rd Author's Name Satoshi Kasai  
3rd Author's Affiliation Fujita Helth University (FJT)
4th Author's Name Satoshi Kondo  
4th Author's Affiliation Muroran Institute of Technology (MuroranIT)
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Speaker Author-1 
Date Time 2026-02-20 16:00:00 
Presentation Time 15 minutes 
Registration for IE 
Paper # ITS2025-80, IE2025-95 
Volume (vol) vol.125 
Number (no) no.355(ITS), no.356(IE) 
Page pp.233-238 
#Pages
Date of Issue 2026-02-12 (ITS, IE) 


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