Paper Abstract and Keywords |
Presentation |
2014-01-26 16:35
Random-forest based spatial normalization using anatomical landmarks from CT images with unknown FOV Kazuma Kikuchi, Toshiyuki Okada (Osaka Univ.), Shouhei Hanaoka, Yoshitaka Masutani (Univ. of Tokyo), Masatoshi Hori, Noriyuki Tomiyama, Yoshinobu Sato (Osaka Univ.) MI2013-87 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
We have proposed the fully automated multi-organ segmentation using computational anatomy modelfrom abdominal CT images. However, this method cannot apply to CT data with different eld of view (FOV) dueto the spatial normalization based on assumption that the FOV of CT image is upper abdomen. In this paper,we propose a method for spatial normalization using anatomical landmarks from CT images with unknown FOV.Given a number of anatomical landmarks, the parameters of the bounding box which determines the normalizationspace are estimated using random forest. The proposed method was evaluated by comparing the segmentationaccuracy using spatial normalization with known FOV. The experimental results using 35 thoracoabdominal CTimages showed that the performance of the proposed method was comparable to the segmentation using spatialnormalization with known FOV. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
machine learning / importance / multiple organ segmentation / feature selection / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 113, no. 410, MI2013-87, pp. 169-173, Jan. 2014. |
Paper # |
MI2013-87 |
Date of Issue |
2014-01-19 (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) |
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MI2013-87 |
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) |
Random-forest based spatial normalization using anatomical landmarks from CT images with unknown FOV |
Sub Title (in English) |
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Keyword(1) |
machine learning |
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importance |
Keyword(3) |
multiple organ segmentation |
Keyword(4) |
feature selection |
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1st Author's Name |
Kazuma Kikuchi |
1st Author's Affiliation |
Osaka University (Osaka Univ.) |
2nd Author's Name |
Toshiyuki Okada |
2nd Author's Affiliation |
Osaka University (Osaka Univ.) |
3rd Author's Name |
Shouhei Hanaoka |
3rd Author's Affiliation |
University of Tokyo (Univ. of Tokyo) |
4th Author's Name |
Yoshitaka Masutani |
4th Author's Affiliation |
University of Tokyo (Univ. of Tokyo) |
5th Author's Name |
Masatoshi Hori |
5th Author's Affiliation |
Osaka University (Osaka Univ.) |
6th Author's Name |
Noriyuki Tomiyama |
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Osaka University (Osaka Univ.) |
7th Author's Name |
Yoshinobu Sato |
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Osaka University (Osaka Univ.) |
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Speaker |
Author-1 |
Date Time |
2014-01-26 16:35:00 |
Presentation Time |
15 minutes |
Registration for |
MI |
Paper # |
MI2013-87 |
Volume (vol) |
vol.113 |
Number (no) |
no.410 |
Page |
pp.169-173 |
#Pages |
5 |
Date of Issue |
2014-01-19 (MI) |
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