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Paper Abstract and Keywords
Presentation 2021-03-15 15:45
Feasibility study of automatic extraction method of coronary artery stationary period using CNN -- Comparison between 1.5T and 3.0T --
Remina Kasai, Yuta Endo, Haruna Shibou, Makoto Amanuma, Kuninori Kobayashi, Shigehide Kuhara (Kyorin Univ.) MI2020-61
Abstract (in Japanese) (See Japanese page) 
(in English) Magnetic resonance coronary angiography (MRCA) requires data acquisition during the stationary period of the coronary arteries. Therefore, accurate detection of this period is important. However, it is currently time-consuming and operator-dependent, because it is visually determined from Cine images. To automatically extract the stationary period, a template-matching method has been developed for tracking the coronary artery position. However, owing to changes in the shape of the coronary arteries during the cardiac phase, it is difficult to detect the position of each coronary artery using a single template. We developed an automatic method to detect the stationary period of coronary arteries using a convolutional neural network (CNN) and investigated its feasibility at 1.5T and 3.0T.
Keyword (in Japanese) (See Japanese page) 
(in English) CNN / MRI / Coronary Artery / Machine Learning / / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 431, MI2020-61, pp. 66-70, March 2021.
Paper # MI2020-61 
Date of Issue 2021-03-08 (MI) 
ISSN Online edition: ISSN 2432-6380
Copyright
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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) Feasibility study of automatic extraction method of coronary artery stationary period using CNN 
Sub Title (in English) Comparison between 1.5T and 3.0T 
Keyword(1) CNN  
Keyword(2) MRI  
Keyword(3) Coronary Artery  
Keyword(4) Machine Learning  
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1st Author's Name Remina Kasai  
1st Author's Affiliation Kyorin University (Kyorin Univ.)
2nd Author's Name Yuta Endo  
2nd Author's Affiliation Kyorin University (Kyorin Univ.)
3rd Author's Name Haruna Shibou  
3rd Author's Affiliation Kyorin University (Kyorin Univ.)
4th Author's Name Makoto Amanuma  
4th Author's Affiliation Kyorin University (Kyorin Univ.)
5th Author's Name Kuninori Kobayashi  
5th Author's Affiliation Kyorin University (Kyorin Univ.)
6th Author's Name Shigehide Kuhara  
6th Author's Affiliation Kyorin University (Kyorin Univ.)
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Speaker Author-1 
Date Time 2021-03-15 15:45:00 
Presentation Time 15 minutes 
Registration for MI 
Paper # MI2020-61 
Volume (vol) vol.120 
Number (no) no.431 
Page pp.66-70 
#Pages
Date of Issue 2021-03-08 (MI) 


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