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Paper Abstract and Keywords
Presentation 2014-01-26 13:30
Newborn brain growth model using manifold learning
Ryosuke Nakano (Univ. of Hyogo), Syoji Kobashi, Kei Kuramoto (Univ. of Hyogo/WPI-IFReC), Yuki Wakata, Kumiko Ando, Reiichi Ishikura (Hyogo College of Medicine), Tomomoto Ishikawa (Ishikawa Hospital), Shozo Hirota (Hyogo College of Medicine), Yutaka Hata (Univ. of Hyogo/Osaka Univ.) MI2013-64
Abstract (in Japanese) (See Japanese page) 
(in English) To develop a computer-aided diagnosis system for neonatal cerebral disorders, some literatures have shown atlas-based methods for segmenting parenchymal region in MR images. Because neonatal cerebrum deforms quickly by natural growth, we desire an atlas growth model. This paper proposes two methods for generating fuzzy object growth model (FOGM), which is an extension of fuzzy object model (FOM). The first method generates a growth-index weighted FOM in which the index is calculated from age. Because the growth index will be different from person to person even though the same age, the second method estimates the growth-index from MR images using manifold learning. To evaluate the proposed methods, we segment the parenchymal region of 16 neonatal subjects (revised age; 0-2 years old). The results showed that FOGM was superior to FOM, and manifold learning based method gave the best accuracy. And, the growth index estimated with manifold learning was significantly correlated with both of age and cerebral volume (p<0.001).
Keyword (in Japanese) (See Japanese page) 
(in English) Newborn Brain / Manifold Learning / Fuzzy Object Model / Fuzzy Object Growth Model / MR Image / / /  
Reference Info. IEICE Tech. Rep., vol. 113, no. 410, MI2013-64, pp. 47-52, Jan. 2014.
Paper # MI2013-64 
Date of Issue 2014-01-19 (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 2014-01-26 - 2014-01-27 
Place (in Japanese) (See Japanese page) 
Place (in English) Bunka Tenbusu Kan 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Computer Assisted Diagnosis and Therapy Based on Computational Anatomy, etc. 
Paper Information
Registration To MI 
Conference Code 2014-01-MI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Newborn brain growth model using manifold learning 
Sub Title (in English)  
Keyword(1) Newborn Brain  
Keyword(2) Manifold Learning  
Keyword(3) Fuzzy Object Model  
Keyword(4) Fuzzy Object Growth Model  
Keyword(5) MR Image  
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Keyword(7)  
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1st Author's Name Ryosuke Nakano  
1st Author's Affiliation University of Hyogo (Univ. of Hyogo)
2nd Author's Name Syoji Kobashi  
2nd Author's Affiliation University of Hyogo/WPI Immunology Frontier Research Center, Osaka University (Univ. of Hyogo/WPI-IFReC)
3rd Author's Name Kei Kuramoto  
3rd Author's Affiliation University of Hyogo/WPI Immunology Frontier Research Center, Osaka University (Univ. of Hyogo/WPI-IFReC)
4th Author's Name Yuki Wakata  
4th Author's Affiliation Hyogo College of Medicine (Hyogo College of Medicine)
5th Author's Name Kumiko Ando  
5th Author's Affiliation Hyogo College of Medicine (Hyogo College of Medicine)
6th Author's Name Reiichi Ishikura  
6th Author's Affiliation Hyogo College of Medicine (Hyogo College of Medicine)
7th Author's Name Tomomoto Ishikawa  
7th Author's Affiliation Ishikawa Hospital (Ishikawa Hospital)
8th Author's Name Shozo Hirota  
8th Author's Affiliation Hyogo College of Medicine (Hyogo College of Medicine)
9th Author's Name Yutaka Hata  
9th Author's Affiliation University of Hyogo/Osaka University (Univ. of Hyogo/Osaka Univ.)
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Speaker Author-1 
Date Time 2014-01-26 13:30:00 
Presentation Time 45 minutes 
Registration for MI 
Paper # MI2013-64 
Volume (vol) vol.113 
Number (no) no.410 
Page pp.47-52 
#Pages
Date of Issue 2014-01-19 (MI) 


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