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Paper Abstract and Keywords
Presentation 2021-03-17 10:15
Automatic Segmentation of bleeding from Laparoscopic Video using Cascade CNN
Shota Yamamoto, Yuichiro Hayashi, Shintaro Morimitsu (Nagoya Univ.), Takayuki Kitasaka (Aichi Institute Tech.), Masahiro Oda (Nagoya Univ.), Nobuyoshi Takeshita, Masaaki Ito (NCC East), Kensaku Mori (Nagoya Univ.) MI2020-88
Abstract (in Japanese) (See Japanese page) 
(in English) We describe a bleeding region segmentation method using cascade CNN from laparoscopic images. In order to support laparoscopic surgery, researches on recognition of the status of surgery by analyzing laparoscopic images are conducted. We focused on the bleeding during surgery and segmented the bleeding region from laparoscopic images using the U-Net. This method has the problem that detailed segmentation is difficult. Therefore, we introduce a cascade processing that uses the detection results of YOLOv3 as the information to be input to the U-Net. In our experiment, bleeding regions were segmented by applying the previous and the proposed method to the video of laparoscopic surgery. As the result, it was confirmed that the detailed bleeding regions could be segmented 10.9% of F-measure higher than the previous method by introducing the cascaded process.
Keyword (in Japanese) (See Japanese page) 
(in English) Laparoscopic surgery / Surgical process analysis / Segmentation / Deep learning / / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 431, MI2020-88, pp. 172-175, March 2021.
Paper # MI2020-88 
Date of Issue 2021-03-08 (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)
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Conference Information
Committee MI  
Conference Date 2021-03-15 - 2021-03-17 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Medical Imaging 
Paper Information
Registration To MI 
Conference Code 2021-03-MI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Automatic Segmentation of bleeding from Laparoscopic Video using Cascade CNN 
Sub Title (in English)  
Keyword(1) Laparoscopic surgery  
Keyword(2) Surgical process analysis  
Keyword(3) Segmentation  
Keyword(4) Deep learning  
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1st Author's Name Shota Yamamoto  
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 Shintaro Morimitsu  
3rd Author's Affiliation Nagoya University (Nagoya Univ.)
4th Author's Name Takayuki Kitasaka  
4th Author's Affiliation Aichi Institute of Technology (Aichi Institute Tech.)
5th Author's Name Masahiro Oda  
5th Author's Affiliation Nagoya University (Nagoya Univ.)
6th Author's Name Nobuyoshi Takeshita  
6th Author's Affiliation National Cancer Center Hospital East (NCC East)
7th Author's Name Masaaki Ito  
7th Author's Affiliation National Cancer Center Hospital East (NCC East)
8th Author's Name Kensaku Mori  
8th Author's Affiliation Nagoya University (Nagoya Univ.)
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Speaker Author-1 
Date Time 2021-03-17 10:15:00 
Presentation Time 15 minutes 
Registration for MI 
Paper # MI2020-88 
Volume (vol) vol.120 
Number (no) no.431 
Page pp.172-175 
#Pages 4 
Date of Issue 2021-03-08 (MI) 

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