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Paper Abstract and Keywords
Presentation 2019-01-23 14:00
[Short Paper] A Lung Cancer Risk Prediction Model based on Clinical Information and Chest CT Images Analyses
Takeru Kageyama, Yoshiki Kawata, Noboru Niki (Tokushima Univ.), Masahiko Kusumoto (National Cancer Center), Hironobu Ohmatsu (Abashiri Prison), Yoshiki Aokage, Takaaki Tsuchida, Yuji Matsumoto (National Cancer Center), Kenji Eguchi (Teikyo Univ.), Masahiro Kaneko (Tokyo Health Service Association Health Support Center) MI2018-98
Abstract (in Japanese) (See Japanese page) 
(in English) Lung cancer accounts for the number of cancer deaths first, and it is on an increasing trend. Although lung cancer CT screening that discovers lung cancer candidates using chest 3-dimensional CT images has been carried out recently as one of the methods for early detection of lung cancer, unnecessary definitive diagnosis is being carried out to non-cancer samples of 20 to 55%. In order to reduce the false positive rate of lung cancer in lung cancer CT screening, multiple malignant risk models have been published that categorize and score nodules in various countries around the world. In this study, we develop high-performance malignant risk models using clinical information and the results of image analysis of Japanese thin section CT images.
Keyword (in Japanese) (See Japanese page) 
(in English) Lung nodule / Chest Chest 3-dimensional CT images / multiple malignant risk model / / / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 412, MI2018-98, pp. 161-163, Jan. 2019.
Paper # MI2018-98 
Date of Issue 2019-01-15 (MI) 
ISSN Online edition: ISSN 2432-6380
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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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Conference Information
Committee MI  
Conference Date 2019-01-22 - 2019-01-23 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English) Medical Image Engineering, Analysis, Recognition, etc. 
Paper Information
Registration To MI 
Conference Code 2019-01-MI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Lung Cancer Risk Prediction Model based on Clinical Information and Chest CT Images Analyses 
Sub Title (in English)  
Keyword(1) Lung nodule  
Keyword(2) Chest Chest 3-dimensional CT images  
Keyword(3) multiple malignant risk model  
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1st Author's Name Takeru Kageyama  
1st Author's Affiliation Tokushima University Graduate School (Tokushima Univ.)
2nd Author's Name Yoshiki Kawata  
2nd Author's Affiliation Tokushima University Graduate School (Tokushima Univ.)
3rd Author's Name Noboru Niki  
3rd Author's Affiliation Tokushima University Graduate School (Tokushima Univ.)
4th Author's Name Masahiko Kusumoto  
4th Author's Affiliation National Cancer Center (National Cancer Center)
5th Author's Name Hironobu Ohmatsu  
5th Author's Affiliation Abashiri Prison (Abashiri Prison)
6th Author's Name Yoshiki Aokage  
6th Author's Affiliation National Cancer Center (National Cancer Center)
7th Author's Name Takaaki Tsuchida  
7th Author's Affiliation National Cancer Center (National Cancer Center)
8th Author's Name Yuji Matsumoto  
8th Author's Affiliation National Cancer Center (National Cancer Center)
9th Author's Name Kenji Eguchi  
9th Author's Affiliation Teikyo University (Teikyo Univ.)
10th Author's Name Masahiro Kaneko  
10th Author's Affiliation Tokyo Health Service Association Health Support Center (Tokyo Health Service Association Health Support Center)
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Speaker Author-1 
Date Time 2019-01-23 14:00:00 
Presentation Time 60 minutes 
Registration for MI 
Paper # MI2018-98 
Volume (vol) vol.118 
Number (no) no.412 
Page pp.161-163 
#Pages
Date of Issue 2019-01-15 (MI) 


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