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) |
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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) |
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Keyword(1) |
Deep Learning |
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Image Captioning |
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Medical |
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CNN |
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LSTM |
Keyword(6) |
Encoder-Decoder |
Keyword(7) |
UMLS |
Keyword(8) |
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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 |
6 |
Date of Issue |
2022-03-03 (PRMU) |