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Presentation 2013-11-07 16:20
Mediastinal Lymph Node Detection Method Based on Radial Structure Tensor and Machine Learning
Hirohisa Oda, Xiongbiao Luo, Yukitaka Nimura, Masahiro Oda (Nagoya Univ.), Takayuki Kitasaka (Aichi Inst. of Tech.), Shingo Iwano (Nagoya Univ.), Hirotoshi Honma (Sapporo Kosei Hospital), Hirotsugu Takabatake (Sapporo Minami-sanjo Hospital), Masaki Mori (Sapporo Kosei Hospital), Hiroshi Natori (Keiwakai Nishioka Hospital), Kensaku Mori (Nagoya Univ.) MI2013-55
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we present a method for detecting mediastinal lymph nodes from 3D chest CT volumes. Mediastinal lymph nodes are observed as blob structures which have higher CT values than the surrounding regions. However, there are lymph nodes adhering other tissue and tissue which have as high CT value as lymph nodes. In the proposed method, a blobness structure enhancement filter based on Radial Structure Tensor (R-BSE) is utilized to obtain candidate regions because the R-BSE is robust for influence of neighboring tissues. The candidate regions are classified into lymph nodes and others by the support vector machine. Shape, location, and CT value of candidate regions are used as feature values. We applied the proposed method to 46 cases of arterial phase 3D CT volumes. The method detected 85.6 % of lymph nodes whose minor axis is no less than 5.0 [mm] with 14.9 FP(False Positive)s per patient. The method also detected 88.5 % of lymph nodes whose minor axis is no less than 10.0 [mm] with 14.8 FPs per patient.
Keyword (in Japanese) (See Japanese page) 
(in English) CAD / Lung Cancer / Support Vector Machine / / / / /  
Reference Info. IEICE Tech. Rep., vol. 113, no. 281, MI2013-55, pp. 51-56, Nov. 2013.
Paper # MI2013-55 
Date of Issue 2013-10-31 (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 2013-11-07 - 2013-11-07 
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 2013-11-MI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Mediastinal Lymph Node Detection Method Based on Radial Structure Tensor and Machine Learning 
Sub Title (in English)  
Keyword(1) CAD  
Keyword(2) Lung Cancer  
Keyword(3) Support Vector Machine  
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1st Author's Name Hirohisa Oda  
1st Author's Affiliation Nagoya University (Nagoya Univ.)
2nd Author's Name Xiongbiao Luo  
2nd Author's Affiliation Nagoya University (Nagoya Univ.)
3rd Author's Name Yukitaka Nimura  
3rd Author's Affiliation Nagoya University (Nagoya Univ.)
4th Author's Name Masahiro Oda  
4th Author's Affiliation Nagoya University (Nagoya Univ.)
5th Author's Name Takayuki Kitasaka  
5th Author's Affiliation Aichi Institute of Technology (Aichi Inst. of Tech.)
6th Author's Name Shingo Iwano  
6th Author's Affiliation Nagoya University (Nagoya Univ.)
7th Author's Name Hirotoshi Honma  
7th Author's Affiliation Sapporo Kosei Hospital (Sapporo Kosei Hospital)
8th Author's Name Hirotsugu Takabatake  
8th Author's Affiliation Sapporo Minami-sanjo Hospital (Sapporo Minami-sanjo Hospital)
9th Author's Name Masaki Mori  
9th Author's Affiliation Sapporo Kosei Hospital (Sapporo Kosei Hospital)
10th Author's Name Hiroshi Natori  
10th Author's Affiliation Keiwakai Nishioka Hospital (Keiwakai Nishioka Hospital)
11th Author's Name Kensaku Mori  
11th Author's Affiliation Nagoya University (Nagoya Univ.)
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Speaker Author-1 
Date Time 2013-11-07 16:20:00 
Presentation Time 30 minutes 
Registration for MI 
Paper # MI2013-55 
Volume (vol) vol.113 
Number (no) no.281 
Page pp.51-56 
#Pages
Date of Issue 2013-10-31 (MI) 


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