Paper Abstract and Keywords |
Presentation |
2017-01-18 16:47
Sparse Shape Modeling in Mandibular Reconstruction with Fibular Segments Riho Kawasaki, Megumi Nakao (Kyoto Univ.), Yuichiro Imai (Rakuwakai Otowa Hospital), Nobuhiro Ueda, Toshihide Hatanaka, Mao Shiba, Tadaaki Kirita (Nara Medical Univ.), Tetsuya Matsuda (Kyoto Univ.) MI2016-120 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Mandibular reconstruction with fibular segments needs preoperative planning for the precise placement of segments. However, recent interactive planning software cannot secure objectivity of the planning and time-consuming trial-and-error processes are required. In this paper, we propose an automated preoperative planning method which employs sparse shape modeling: in this modeling, we select a small subset of the data whose features are similar to the test data from a prepared preoperative planning dataset to make an example of reconstruction via a linear combination of the data. We conducted experiments using 120 data planned by surgeons and verified the effectiveness of the proposed method. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
sparse modeling / automated planning / mandibular reconstruction / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 116, no. 393, MI2016-120, pp. 195-200, Jan. 2017. |
Paper # |
MI2016-120 |
Date of Issue |
2017-01-11 (MI) |
ISSN |
Print edition: ISSN 0913-5685 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 |
MI2016-120 |
|