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Paper Abstract and Keywords
Presentation 2022-01-27 13:54
[Short Paper] Case-based Similar Image Retrieval for Pathological Images of Malignant Lymphoma Using Deep Metric Learning
Noriaki Hashimoto (RIKEN), Yusuke Takagi, Hiroki Masuda (NITech), Hiroaki Miyoshi, Kei Kohno, Miharu Nagaishi, Kensaku Sato, Koichi Ohshima (Kurume Univ.), Hidekata Hontani (NITech), Ichiro Takeuchi (NITech/RIKEN) MI2021-78
Abstract (in Japanese) (See Japanese page) 
(in English) We propose a novel method of case-based similar image retrieval for histopathological images of malignant lymphoma. We employ contrastive distance metric learning to incorporate immunohistochemical staining patterns as useful supervised information for defining appropriate similarity between heterogeneous malignant lymphoma cases. Moreover, we realize a case-based image retrieval method that can automatically focus on tumor-specific regions in the entire tissue slide using attention-based multiple instance learning. In the experiment with 249 malignant lymphoma patients, we confirmed that the proposed method exhibited higher evaluation measures than the baseline case-based similar image retrieval methods.
Keyword (in Japanese) (See Japanese page) 
(in English) Pathological image / Case-based similar image retrieval / Malignant lymphoma / Distance metric learning / Immunohistochemical stain / / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 347, MI2021-78, pp. 144-145, Jan. 2022.
Paper # MI2021-78 
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)
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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) Case-based Similar Image Retrieval for Pathological Images of Malignant Lymphoma Using Deep Metric Learning 
Sub Title (in English)  
Keyword(1) Pathological image  
Keyword(2) Case-based similar image retrieval  
Keyword(3) Malignant lymphoma  
Keyword(4) Distance metric learning  
Keyword(5) Immunohistochemical stain  
Keyword(6)  
Keyword(7)  
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1st Author's Name Noriaki Hashimoto  
1st Author's Affiliation RIKEN (RIKEN)
2nd Author's Name Yusuke Takagi  
2nd Author's Affiliation Nagoya Institute of Technology (NITech)
3rd Author's Name Hiroki Masuda  
3rd Author's Affiliation Nagoya Institute of Technology (NITech)
4th Author's Name Hiroaki Miyoshi  
4th Author's Affiliation Kurume University (Kurume Univ.)
5th Author's Name Kei Kohno  
5th Author's Affiliation Kurume University (Kurume Univ.)
6th Author's Name Miharu Nagaishi  
6th Author's Affiliation Kurume University (Kurume Univ.)
7th Author's Name Kensaku Sato  
7th Author's Affiliation Kurume University (Kurume Univ.)
8th Author's Name Koichi Ohshima  
8th Author's Affiliation Kurume University (Kurume Univ.)
9th Author's Name Hidekata Hontani  
9th Author's Affiliation Nagoya Institute of Technology (NITech)
10th Author's Name Ichiro Takeuchi  
10th Author's Affiliation Nagoya Institute of Technology/RIKEN (NITech/RIKEN)
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Speaker Author-1 
Date Time 2022-01-27 13:54:00 
Presentation Time 13 minutes 
Registration for MI 
Paper # MI2021-78 
Volume (vol) vol.121 
Number (no) no.347 
Page pp.144-145 
#Pages 2 
Date of Issue 2022-01-18 (MI) 

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