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Paper Abstract and Keywords
Presentation 2023-03-06 16:38
An Investigation of Effectiveness of Organ Features in Automated Anatomical Labeling Using Graph Neural Networks
Tomoya Deguchi, Yuichiro Hayashi, Masahiro Oda (Nagoya Univ), Takayuki Kitasaka (Aichi Institute of Tech), Kazunari Misawa (Aichi Cancer Center Hospital), Kensaku Mori (Nagoya Univ/NII) MI2022-94
Abstract (in Japanese) (See Japanese page) 
(in English) In this study, we investigate important organ features for automated anatomical labeling of abdominal arteries using Graph Neural Networks. It is important for physicians to understand the anatomical structures of their patients in diagnosis and treatment. On the other hand, abdominal blood vessel structures are complex and difficult to understand. Therefore, several researches have been conducted on automated labeling methods for anatomical name of abdominal arteries to assist physicians in understanding vessel structures. However, it is still difficult to label hepatic arteries and gastric arteries. In this study, we label blood vessel name by changing the organ features and comparing the results to investigate the organ features that are effective in automated anatomical labeling of abdominal arteries.
Keyword (in Japanese) (See Japanese page) 
(in English) blood vessel / CT volume / anatomical names recognition / blood vessel structures analysis / / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 417, MI2022-94, pp. 105-110, March 2023.
Paper # MI2022-94 
Date of Issue 2023-02-27 (MI) 
ISSN Online edition: ISSN 2432-6380
Copyright
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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)
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Conference Information
Committee MI  
Conference Date 2023-03-06 - 2023-03-07 
Place (in Japanese) (See Japanese page) 
Place (in English) OKINAWA SEINENKAIKAN 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To MI 
Conference Code 2023-03-MI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) An Investigation of Effectiveness of Organ Features in Automated Anatomical Labeling Using Graph Neural Networks 
Sub Title (in English)  
Keyword(1) blood vessel  
Keyword(2) CT volume  
Keyword(3) anatomical names recognition  
Keyword(4) blood vessel structures analysis  
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1st Author's Name Tomoya Deguchi  
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 Takayuki Kitasaka  
4th Author's Affiliation Aichi Institute of Technology (Aichi Institute of Tech)
5th Author's Name Kazunari Misawa  
5th Author's Affiliation Aichi Cancer Center Hospital (Aichi Cancer Center Hospital)
6th Author's Name Kensaku Mori  
6th Author's Affiliation Nagoya University/National Institute of Informatics (Nagoya Univ/NII)
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Speaker Author-1 
Date Time 2023-03-06 16:38:00 
Presentation Time 13 minutes 
Registration for MI 
Paper # MI2022-94 
Volume (vol) vol.122 
Number (no) no.417 
Page pp.105-110 
#Pages
Date of Issue 2023-02-27 (MI) 


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