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Paper Abstract and Keywords
Presentation 2023-07-03 15:00
Anchor Free Universal Lesion Detector in CT images using YOLOv7
Sena Shimizu, Minoru Nakazawa (KIT) MI2023-12
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, there has been active research on Universal Lesion Detection(ULD) using Deep Learning models to detect different types of lesions in various organs of the body with a single pre-trained model. However, conventional ULDs focus only on improving detection sensitivity and most of them required computational complexity. On the other hand, recent Object Detection Networks based on Deep Learning have achieved high object detection accuracy with low computational complexity. In this study, we present to ULDs using YOLOv7(You Only Look Once version 7) which relatively has high object detection accuracy and low computational complexity. As a result, we achieved the same level of Lesion Detection sensitivity in the DeepLesion Dataset with less computational complexity than in previous works.
Keyword (in Japanese) (See Japanese page) 
(in English) Computed Tomography(CT) / Universal Lesion Detection / Computer Vision / / / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 96, MI2023-12, pp. 14-19, July 2023.
Paper # MI2023-12 
Date of Issue 2023-06-26 (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 MI2023-12

Conference Information
Committee MI  
Conference Date 2023-07-03 - 2023-07-03 
Place (in Japanese) (See Japanese page) 
Place (in English) Tohoku Univ. Sakura Hall 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Medical Imaging, etc. 
Paper Information
Registration To MI 
Conference Code 2023-07-MI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Anchor Free Universal Lesion Detector in CT images using YOLOv7 
Sub Title (in English)  
Keyword(1) Computed Tomography(CT)  
Keyword(2) Universal Lesion Detection  
Keyword(3) Computer Vision  
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1st Author's Name Sena Shimizu  
1st Author's Affiliation Kanazawa Institute of Technology (KIT)
2nd Author's Name Minoru Nakazawa  
2nd Author's Affiliation Kanazawa Institute of Technology (KIT)
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Speaker Author-1 
Date Time 2023-07-03 15:00:00 
Presentation Time 30 minutes 
Registration for MI 
Paper # MI2023-12 
Volume (vol) vol.123 
Number (no) no.96 
Page pp.14-19 
#Pages 6 
Date of Issue 2023-06-26 (MI) 

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