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Paper Abstract and Keywords
Presentation 2014-01-26 13:30
An Improvement of Automated Lymph Node Detection Method from 3D Abdominal X-ray CT Images using Feature Selection Method
Yoshihiko Nakamura (Nagoya Univ.), Takayuki Kitasaka, Shinji Mizuno (Aichi Inst. of Tech.), Kazuhiro Furukawa, Hidemi Goto, Michitaka Fujiwara (Nagoya Univ.), Kazunari Misawa (Aichi Cancer Center Hospital), Masaaki Ito (National Cancer Center Hospital East), Shigeru Nawano (IUHW Mita Hospital), Kensaku Mori (Nagoya Univ.) MI2013-72
Abstract (in Japanese) (See Japanese page) 
(in English) We have been developing automatical abdominal lymph node detection methods to aid pre-operating diagnosis for surgery of colorectal or stomach cancers. Our purpose is to achieve the aid for resection area decision in pre-operative diagnosis and the aid for intra-operation by displaying the detected lymph nodes. We have proposed methods for detecting lymph nodes based on estimation and classification of local intensity structure. In this paper, we improve false positive reduction process using the feature selection methods. By applying the proposed method to 28 abdominal 3D CT images, we can detect 68 of 95 lymph nodes with 12.5 false positive per case.
Keyword (in Japanese) (See Japanese page) 
(in English) computer aided surgery / lymph node detection / local intensity structure analysis / feature selection / / / /  
Reference Info. IEICE Tech. Rep., vol. 113, no. 410, MI2013-72, pp. 85-90, Jan. 2014.
Paper # MI2013-72 
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) An Improvement of Automated Lymph Node Detection Method from 3D Abdominal X-ray CT Images using Feature Selection Method 
Sub Title (in English)  
Keyword(1) computer aided surgery  
Keyword(2) lymph node detection  
Keyword(3) local intensity structure analysis  
Keyword(4) feature selection  
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1st Author's Name Yoshihiko Nakamura  
1st Author's Affiliation Nagoya University (Nagoya Univ.)
2nd Author's Name Takayuki Kitasaka  
2nd Author's Affiliation Aichi Institute of Technology (Aichi Inst. of Tech.)
3rd Author's Name Shinji Mizuno  
3rd Author's Affiliation Aichi Institute of Technology (Aichi Inst. of Tech.)
4th Author's Name Kazuhiro Furukawa  
4th Author's Affiliation Nagoya University (Nagoya Univ.)
5th Author's Name Hidemi Goto  
5th Author's Affiliation Nagoya University (Nagoya Univ.)
6th Author's Name Michitaka Fujiwara  
6th Author's Affiliation Nagoya University (Nagoya Univ.)
7th Author's Name Kazunari Misawa  
7th Author's Affiliation Aichi Cancer Center Hospital (Aichi Cancer Center Hospital)
8th Author's Name Masaaki Ito  
8th Author's Affiliation National Cancer Center Hospital East (National Cancer Center Hospital East)
9th Author's Name Shigeru Nawano  
9th Author's Affiliation International University of Health and Welfare Mita Hospital (IUHW Mita Hospital)
10th Author's Name Kensaku Mori  
10th Author's Affiliation Nagoya University (Nagoya Univ.)
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Speaker Author-1 
Date Time 2014-01-26 13:30:00 
Presentation Time 45 minutes 
Registration for MI 
Paper # MI2013-72 
Volume (vol) vol.113 
Number (no) no.410 
Page pp.85-90 
#Pages
Date of Issue 2014-01-19 (MI) 


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