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| Presentation | 2012-01-20 11:25 Detection of the liver hemangioma from 3D abdominal CT images by using local intensity features and multi-class classifier Yoshitaka Sakamoto, Masahiro Oda (Nagoya Univ), Takayuki Kitasaka (AIT), Shigeru Nawano (IHW), Kensaku Mori (Nagoya Univ)  MI2011-146 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In this paper, we propose a method for detecting hemangioma from four-phases contrasted 3D abdominal CT images. In our method, candidate regions of the liver hemangioma are detected from a portal phase CT image. The candidate regions of the liver hemangioma are obtained by classifying voxels based on the posterior probability of each voxel in a liver region. Since false positives of detection results usually include blood vessel regions, we remove the blood vessel regions in the liver from the candidate regions. Then, we calculate a feature value vector at each voxel in the candidate regions. Feature value vectors are calculated by using various filters such as median, gaussian, and blob enhancement filters. A category of each feature value vector is determined by a multi-class classifier. Finally, we obtain regions whose category is classified as the liver hemangioma. We apply this method to 15 cases of abdominal CT images. Recall rates of the segmentation accuracy and the number of False Positives were 83.3% and 15.4 per case, respectively. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | abdominal CT image / liver hemangioma / computer assisted detection / / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 111, no. 389, MI2011-146, pp. 383-388, Jan. 2012. | |
| Paper # | MI2011-146 | |
| Date of Issue | 2012-01-12 (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 | MI2011-146 |
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| Conference Information | |
| Committee | MI |
| Conference Date | 2012-01-19 - 2012-01-20 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | MI |
| Conference Code | 2012-01-MI |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Detection of the liver hemangioma from 3D abdominal CT images by using local intensity features and multi-class classifier |
| Sub Title (in English) | |
| Keyword(1) | abdominal CT image |
| Keyword(2) | liver hemangioma |
| Keyword(3) | computer assisted detection |
| Keyword(4) | |
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| 1st Author's Name | Yoshitaka Sakamoto |
| 1st Author's Affiliation | Nagoya University (Nagoya Univ) |
| 2nd Author's Name | Masahiro Oda |
| 2nd Author's Affiliation | Nagoya University (Nagoya Univ) |
| 3rd Author's Name | Takayuki Kitasaka |
| 3rd Author's Affiliation | Aichi Institute of Technology (AIT) |
| 4th Author's Name | Shigeru Nawano |
| 4th Author's Affiliation | International University of Health and Welfare (IHW) |
| 5th Author's Name | Kensaku Mori |
| 5th Author's Affiliation | Nagoya University (Nagoya Univ) |
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| Speaker | Author-1 |
| Date Time | 2012-01-20 11:25:00 |
| Presentation Time | 30 minutes |
| Registration for | MI |
| Paper # | MI2011-146 |
| Volume (vol) | vol.111 |
| Number (no) | no.389 |
| Page | pp.383-388 |
| #Pages | 6 |
| Date of Issue | 2012-01-12 (MI) |
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