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Paper Abstract and Keywords
Presentation 2022-03-10 10:40
Medical Image Captioning with Information based on Medical Concepts
Riku Tsuneda, Tetsuya Asakawa (TUT), Kazuki Shimizu, Takuyuki Komoda (THC), Masaki Aono (TUT) PRMU2021-64
Abstract (in Japanese) (See Japanese page) 
(in English) Image Captioning for medical images is expected to augment the judgment of doctors and serve as a second opinion. Medical Image Captioning is a challenging task for accurate caption generation because rich medical terminologies are entailed with captioning.In this paper,we propose a method for medical image captioning by leveraging information from medical concepts.The experiments using the CLEF2021MedicalCaptionTask dataset show that the proposed method outperforms the base line method with "Show,Attend and Tell",in terms of BLEU evaluation metrics.
Keyword (in Japanese) (See Japanese page) 
(in English) Deep Learning / Image Captioning / Medical / CNN / LSTM / Encoder-Decoder / UMLS /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 427, PRMU2021-64, pp. 25-30, March 2022.
Paper # PRMU2021-64 
Date of Issue 2022-03-03 (PRMU) 
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 PRMU2021-64

Conference Information
Committee PRMU IPSJ-CVIM  
Conference Date 2022-03-10 - 2022-03-11 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Differentiable rendering 
Paper Information
Registration To PRMU 
Conference Code 2022-03-PRMU-CVIM 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Medical Image Captioning with Information based on Medical Concepts 
Sub Title (in English)  
Keyword(1) Deep Learning  
Keyword(2) Image Captioning  
Keyword(3) Medical  
Keyword(4) CNN  
Keyword(5) LSTM  
Keyword(6) Encoder-Decoder  
Keyword(7) UMLS  
Keyword(8)  
1st Author's Name Riku Tsuneda  
1st Author's Affiliation Toyohashi University of Technology (TUT)
2nd Author's Name Tetsuya Asakawa  
2nd Author's Affiliation Toyohashi University of Technology (TUT)
3rd Author's Name Kazuki Shimizu  
3rd Author's Affiliation Toyohashi Heart Center (THC)
4th Author's Name Takuyuki Komoda  
4th Author's Affiliation Toyohashi Heart Center (THC)
5th Author's Name Masaki Aono  
5th Author's Affiliation Toyohashi University of Technology (TUT)
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Speaker Author-1 
Date Time 2022-03-10 10:40:00 
Presentation Time 15 minutes 
Registration for PRMU 
Paper # PRMU2021-64 
Volume (vol) vol.121 
Number (no) no.427 
Page pp.25-30 
#Pages
Date of Issue 2022-03-03 (PRMU) 


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