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| Presentation | 2013-01-24 17:05 Automated segmentation of the upper digestive tract from abdominal contrast-enhanced CT data using hierarchical statistical modeling of organ inter-relations Shunta Hirayama, Toshiyuki Okada, Masatoshi Hori, Noriyuki Tomiyama, Yoshinobu Sato (Osaka Univ.)  MI2012-91 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | We have studied the automatic segmentation of multi-organ region from abdominal CT images ever. In previous work, we have proposed the automatic segmentation of multiple organ region by performing a hierarchical statistical modeling using a relationship between organs. In this paper, we have proposed automatically segmentation of the upper digestive tract from abdominal contrast-enhanced CT using segmented multi organs so far. Segment and compare the esophagus, stomach and duodenum using hierarchical statistical modeling which is our proposed method, and conventional statistical atlas method. They were evaluated quantitatively by Jaccard index and the surface distance error of the segmented region and correct region data. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | hierarchical statistical modeling / Prediction statistical atlas / gastroduodenal / esophagus / semi-supervised learning / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 112, no. 411, MI2012-91, pp. 149-154, Jan. 2013. | |
| Paper # | MI2012-91 | |
| Date of Issue | 2013-01-17 (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 | MI2012-91 |
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| Conference Information | |
| Committee | MI |
| Conference Date | 2013-01-24 - 2013-01-25 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Bunka Tenbusu Kan |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Computational anatomy and its application to computer assisted diagnosis and therapy, etc |
| Paper Information | |
| Registration To | MI |
| Conference Code | 2013-01-MI |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Automated segmentation of the upper digestive tract from abdominal contrast-enhanced CT data using hierarchical statistical modeling of organ inter-relations |
| Sub Title (in English) | |
| Keyword(1) | hierarchical statistical modeling |
| Keyword(2) | Prediction statistical atlas |
| Keyword(3) | gastroduodenal |
| Keyword(4) | esophagus |
| Keyword(5) | semi-supervised learning |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Shunta Hirayama |
| 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 | Masatoshi Hori |
| 3rd Author's Affiliation | Osaka University (Osaka Univ.) |
| 4th Author's Name | Noriyuki Tomiyama |
| 4th Author's Affiliation | Osaka University (Osaka Univ.) |
| 5th Author's Name | Yoshinobu Sato |
| 5th Author's Affiliation | Osaka University (Osaka Univ.) |
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| Speaker | Author-1 |
| Date Time | 2013-01-24 17:05:00 |
| Presentation Time | 15 minutes |
| Registration for | MI |
| Paper # | MI2012-91 |
| Volume (vol) | vol.112 |
| Number (no) | no.411 |
| Page | pp.149-154 |
| #Pages | 6 |
| Date of Issue | 2013-01-17 (MI) |
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