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Paper Abstract and Keywords
Presentation 2019-01-22 13:20
[Short Paper] Differences of Segmentation Results by Three Training Data for Cartilage Extraction in Knee MR Images Using Deep Learning
Ryoma Aoki, Takeshi Hara (Gifu Univ), Taiki Nozaki, Masaki Matsusako (Dept.of Radiol.,St.Luke's Hosp.), Xiangrong Zhou, Hiroshi Fujita (Gifu Univ) MI2018-76
Abstract (in Japanese) (See Japanese page) 
(in English) Accurate grasp of cartilage area is important for diagnosis and treatment related to arthropathy diseases. In recent years, the importance of the quantitative evaluation index of the cartilage state has been noted in the diagnosis related to knee articular cartilage. The purpose of this research is to develop an automatic extraction method of cartilage region using deep learning. FCN-32s, FCN-16s and FCN-8s were used for learning from each teacher data of 20 normal MR images in which 2 doctors drew a cartilage area, and comparison was made by t-test with interobserver and intraobserver correspondence. As a result, it was suggested that there was a significant difference in learning result, and comparison of cartilage region extraction accuracy could be done.
Keyword (in Japanese) (See Japanese page) 
(in English) Knee MR image / cartilage / segmentation / FCN / / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 412, MI2018-76, pp. 63-64, Jan. 2019.
Paper # MI2018-76 
Date of Issue 2019-01-15 (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 MI2018-76

Conference Information
Committee MI  
Conference Date 2019-01-22 - 2019-01-23 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English) Medical Image Engineering, Analysis, Recognition, etc. 
Paper Information
Registration To MI 
Conference Code 2019-01-MI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Differences of Segmentation Results by Three Training Data for Cartilage Extraction in Knee MR Images Using Deep Learning 
Sub Title (in English)  
Keyword(1) Knee MR image  
Keyword(2) cartilage  
Keyword(3) segmentation  
Keyword(4) FCN  
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1st Author's Name Ryoma Aoki  
1st Author's Affiliation Gifu University (Gifu Univ)
2nd Author's Name Takeshi Hara  
2nd Author's Affiliation Gifu University (Gifu Univ)
3rd Author's Name Taiki Nozaki  
3rd Author's Affiliation Department of Radiology,St.Luke's International Hospitai (Dept.of Radiol.,St.Luke's Hosp.)
4th Author's Name Masaki Matsusako  
4th Author's Affiliation Department of Radiology,St.Luke's International Hospitai (Dept.of Radiol.,St.Luke's Hosp.)
5th Author's Name Xiangrong Zhou  
5th Author's Affiliation Gifu University (Gifu Univ)
6th Author's Name Hiroshi Fujita  
6th Author's Affiliation Gifu University (Gifu Univ)
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Speaker Author-1 
Date Time 2019-01-22 13:20:00 
Presentation Time 50 minutes 
Registration for MI 
Paper # MI2018-76 
Volume (vol) vol.118 
Number (no) no.412 
Page pp.63-64 
#Pages 2 
Date of Issue 2019-01-15 (MI) 

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