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Paper Abstract and Keywords
Presentation 2019-01-23 10:55
Semi-Automated Segmentation of Rotator Cuff in MR Images with Statistical Shape Model
Kazuki Ishiro, Kento Morita, Manabu Nii (Univ. of Hyogo), Tomoyuki Muto, Hiroshi Tanaka, Hiroaki Inui (Nobuhara Hospital), Syoji Kobashi (Univ. of Hyogo), Katsuya Nobuhara (Nobuhara Hospital) MI2018-91
Abstract (in Japanese) (See Japanese page) 
(in English) A surgical method to repair rotator cuff tear is decided by a tear form. To diagnose the tear form, we previously proposed a method to reconstruct 3-D shoulder rotator cuff shape from a region manually segmented by an orthopedic surgeon. However, the reconstructed 3-D shape was strongly dependent on the segmented region. Therefore, this paper proposes a method for semi-automated segmentation of rotator cuff in MR images. A rotator cuff’s statistical shape model (SSM) is utilized for the segmentation. The SSM has been constructed by applying principal component analysis to normalized rotator cuff region. The shape parameters of SSM has been estimated from MR image signals to segment the region. The mean segmentation accuracy calculated by Dice coefficient was 0.683, and the mean error distance was 2.307 mm.
Keyword (in Japanese) (See Japanese page) 
(in English) Shoulder rotator cuff / Principal component analysis / Statistical shape model / Segmentation / / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 412, MI2018-91, pp. 131-136, Jan. 2019.
Paper # MI2018-91 
Date of Issue 2019-01-15 (MI) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
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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 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) Semi-Automated Segmentation of Rotator Cuff in MR Images with Statistical Shape Model 
Sub Title (in English)  
Keyword(1) Shoulder rotator cuff  
Keyword(2) Principal component analysis  
Keyword(3) Statistical shape model  
Keyword(4) Segmentation  
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1st Author's Name Kazuki Ishiro  
1st Author's Affiliation University of Hyogo (Univ. of Hyogo)
2nd Author's Name Kento Morita  
2nd Author's Affiliation University of Hyogo (Univ. of Hyogo)
3rd Author's Name Manabu Nii  
3rd Author's Affiliation University of Hyogo (Univ. of Hyogo)
4th Author's Name Tomoyuki Muto  
4th Author's Affiliation Nobuhara Hospital and Institute of Biomechanics (Nobuhara Hospital)
5th Author's Name Hiroshi Tanaka  
5th Author's Affiliation Nobuhara Hospital and Institute of Biomechanics (Nobuhara Hospital)
6th Author's Name Hiroaki Inui  
6th Author's Affiliation Nobuhara Hospital and Institute of Biomechanics (Nobuhara Hospital)
7th Author's Name Syoji Kobashi  
7th Author's Affiliation University of Hyogo (Univ. of Hyogo)
8th Author's Name Katsuya Nobuhara  
8th Author's Affiliation Nobuhara Hospital and Institute of Biomechanics (Nobuhara Hospital)
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Speaker
Date Time 2019-01-23 10:55:00 
Presentation Time 15 
Registration for MI 
Paper # IEICE-MI2018-91 
Volume (vol) IEICE-118 
Number (no) no.412 
Page pp.131-136 
#Pages IEICE-6 
Date of Issue IEICE-MI-2019-01-15 


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