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Paper Abstract and Keywords
Presentation 2020-01-29 13:20
[Short Paper] Automatic segmentation of malignant tumors using PET/CT images and statistical images
Manami Haga, Takeshi Hara (Gifu Univ.), Satoshi Ito, Masaya Kato (Daiyukai Hospital), Masaki Matsusako (St.Luke's Hospital), Zhou Xiangrong (Gifu Univ.), Tetsuro Katafuchi (Gifu Univ. of Medical Science), Hiroshi Fujita (Gifu Univ.) MI2019-83
Abstract (in Japanese) (See Japanese page) 
(in English) The purpose of this study was to develop an automated detection system of tumors in FDG-PET/CT images. In this work, an anatomical standardization process was performed based on landmarks on organs’ surfaces determined by semi-automated GraphCut method on CT images. After the anatomical standardization of FDG-PET images, the Z-score images in each patient were obtained from the mean and the standard deviation images. Suspicious regions on FDG-PET images were determined using a dynamic thresholding approach and labeling methods. An convolutional neural network was used to discriminate the remaining regions as false-positive areas. Detection performance was evaluated 65 PET/CT cases. The performance was 79.8% sensitivity with 22.7 marks per case.
Keyword (in Japanese) (See Japanese page) 
(in English) PET / SUV / Z-score / / / / /  
Reference Info. IEICE Tech. Rep., vol. 119, no. 399, MI2019-83, pp. 77-81, Jan. 2020.
Paper # MI2019-83 
Date of Issue 2020-01-22 (MI) 
ISSN 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)
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Conference Information
Committee MI  
Conference Date 2020-01-29 - 2020-01-30 
Place (in Japanese) (See Japanese page) 
Place (in English) OKINAWAKEN SEINENKAIKAN 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Medical Image Engineering, Analysis, Recognition, etc. 
Paper Information
Registration To MI 
Conference Code 2020-01-MI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Automatic segmentation of malignant tumors using PET/CT images and statistical images 
Sub Title (in English)  
Keyword(1) PET  
Keyword(2) SUV  
Keyword(3) Z-score  
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1st Author's Name Manami Haga  
1st Author's Affiliation Gifu University (Gifu Univ.)
2nd Author's Name Takeshi Hara  
2nd Author's Affiliation Gifu University (Gifu Univ.)
3rd Author's Name Satoshi Ito  
3rd Author's Affiliation Daiyukai General Hospital (Daiyukai Hospital)
4th Author's Name Masaya Kato  
4th Author's Affiliation Daiyukai General Hospital (Daiyukai Hospital)
5th Author's Name Masaki Matsusako  
5th Author's Affiliation St.Luke's International Hospital (St.Luke's Hospital)
6th Author's Name Zhou Xiangrong  
6th Author's Affiliation Gifu University (Gifu Univ.)
7th Author's Name Tetsuro Katafuchi  
7th Author's Affiliation Gifu University of Medical Science (Gifu Univ. of Medical Science)
8th Author's Name Hiroshi Fujita  
8th Author's Affiliation Gifu University (Gifu Univ.)
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Speaker Author-1 
Date Time 2020-01-29 13:20:00 
Presentation Time 30 minutes 
Registration for MI 
Paper # MI2019-83 
Volume (vol) vol.119 
Number (no) no.399 
Page pp.77-81 
#Pages 5 
Date of Issue 2020-01-22 (MI) 

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