| 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 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 |
ITS2025-80 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) |
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| 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) |
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| Keyword(1) |
LLM |
| Keyword(2) |
VLM |
| Keyword(3) |
Chest X-ray |
| Keyword(4) |
report generation |
| Keyword(5) |
Llama |
| Keyword(6) |
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| Keyword(7) |
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| Keyword(8) |
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| 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 |
6 |
| Date of Issue |
2026-02-12 (ITS, IE) |