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Paper Abstract and Keywords
Presentation 2022-01-26 11:05
Study on automatic generation of COVID-19 related radiology reports from chest CT images
Shinji Okazaki, Yuichiro Hayashi, Masahiro Oda (Nagoya Univ.), Masahiro Hashimoto, Masahiro Jinzaki (Keio Univ.), Toshiaki Akashi, Shigeki Aoki (Juntendo Univ.), Kensaku Mori (Nagoya Univ./NII) MI2021-57
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we describe a study on automatic generation of COVID-19 related radiology reports from chest CT images. The radiology reports made by radiologists when CT images are taken contain important information. However, burdens on radiologists are increasing due to a wider imaging range of enhanced performance of CT imaging devices and an increase in the number of CT scans. Automatic radiology reports generations are needed to reduce burdens on radiologists. In this study, we propose a method for automatic generation of COVID-19 related radiology reports from chest CT images based on image classification results by a CNN-LSTM model. We achieved 0.29 BLEU scores in an experiment on radiology reports generation.
Keyword (in Japanese) (See Japanese page) 
(in English) natural language processing / radiology report / automatic generation / image classification / / / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 347, MI2021-57, pp. 49-54, Jan. 2022.
Paper # MI2021-57 
Date of Issue 2022-01-18 (MI) 
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 MI2021-57

Conference Information
Committee MI  
Conference Date 2022-01-25 - 2022-01-27 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To MI 
Conference Code 2022-01-MI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Study on automatic generation of COVID-19 related radiology reports from chest CT images 
Sub Title (in English)  
Keyword(1) natural language processing  
Keyword(2) radiology report  
Keyword(3) automatic generation  
Keyword(4) image classification  
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1st Author's Name Shinji Okazaki  
1st Author's Affiliation Nagoya University (Nagoya Univ.)
2nd Author's Name Yuichiro Hayashi  
2nd Author's Affiliation Nagoya University (Nagoya Univ.)
3rd Author's Name Masahiro Oda  
3rd Author's Affiliation Nagoya University (Nagoya Univ.)
4th Author's Name Masahiro Hashimoto  
4th Author's Affiliation Keio University (Keio Univ.)
5th Author's Name Masahiro Jinzaki  
5th Author's Affiliation Keio University (Keio Univ.)
6th Author's Name Toshiaki Akashi  
6th Author's Affiliation Juntendo University (Juntendo Univ.)
7th Author's Name Shigeki Aoki  
7th Author's Affiliation Juntendo University (Juntendo Univ.)
8th Author's Name Kensaku Mori  
8th Author's Affiliation Nagoya University/National Institute of Informatics (Nagoya Univ./NII)
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Speaker Author-1 
Date Time 2022-01-26 11:05:00 
Presentation Time 13 minutes 
Registration for MI 
Paper # MI2021-57 
Volume (vol) vol.121 
Number (no) no.347 
Page pp.49-54 
#Pages 6 
Date of Issue 2022-01-18 (MI) 

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