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Paper Abstract and Keywords
Presentation 2024-03-04 13:40
Multi-Organ Segmentation from 3D Abdominal CT Images Using Blood Vessel Enhanced Images and AutoML
Mana Ohno, Shen Chen (Nagoya Univ.), Holger R. Roth (NVIDIA Corp.), Masahiro Oda, Yuichiro Hayashi (Nagoya Univ.), Kazunari Misawa (Aichi Cancer Center), Kensaku Mori (Nagoya Univ.) MI2023-78
Abstract (in Japanese) (See Japanese page) 
(in English) Multi-organ segmentation is an essential method for the development of computer-aided diagnosis and surgery systems. In the previous methods, while segmentation accuracies of organs having simple shapes were high such as the liver and spleen, segmentation accuracies of organs having complex shapes such as blood vessels were low. In this study, we propose a multi-organ segmentation method using vessel enhancement images, which the tubular structures of 3D CT images are enhanced. For vessel enhancement images, it is necessary to set a scale parameter that determine the size of tubular structures to be enhanced. To find the optimal parameter, hyperparameter search was performed using AutoML. We extracted multi-organ regions using vessel enhancement images generated by the scale parameter selected based on hyperparameter search. The Dice scores of artery and portal vein were 86.10% and 72.88% respectively.
Keyword (in Japanese) (See Japanese page) 
(in English) Segmentation / Auto3DSeg / Multi-organ Segmentation / / / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 411, MI2023-78, pp. 152-155, March 2024.
Paper # MI2023-78 
Date of Issue 2024-02-25 (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 MI2023-78

Conference Information
Committee MI  
Conference Date 2024-03-03 - 2024-03-04 
Place (in Japanese) (See Japanese page) 
Place (in English) OKINAWAKEN SEINENKAIKAN 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Medical Imaging, etc. 
Paper Information
Registration To MI 
Conference Code 2024-03-MI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Multi-Organ Segmentation from 3D Abdominal CT Images Using Blood Vessel Enhanced Images and AutoML 
Sub Title (in English)  
Keyword(1) Segmentation  
Keyword(2) Auto3DSeg  
Keyword(3) Multi-organ Segmentation  
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1st Author's Name Mana Ohno  
1st Author's Affiliation Nagoya University (Nagoya Univ.)
2nd Author's Name Shen Chen  
2nd Author's Affiliation Nagoya University (Nagoya Univ.)
3rd Author's Name Holger R. Roth  
3rd Author's Affiliation NVIDIA Corporation (NVIDIA Corp.)
4th Author's Name Masahiro Oda  
4th Author's Affiliation Nagoya University (Nagoya Univ.)
5th Author's Name Yuichiro Hayashi  
5th Author's Affiliation Nagoya University (Nagoya Univ.)
6th Author's Name Kazunari Misawa  
6th Author's Affiliation Aichi Cancer Center (Aichi Cancer Center)
7th Author's Name Kensaku Mori  
7th Author's Affiliation Nagoya University (Nagoya Univ.)
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Speaker Author-1 
Date Time 2024-03-04 13:40:00 
Presentation Time 12 minutes 
Registration for MI 
Paper # MI2023-78 
Volume (vol) vol.123 
Number (no) no.411 
Page pp.152-155 
#Pages 4 
Date of Issue 2024-02-25 (MI) 

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