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Paper Abstract and Keywords
Presentation 2018-05-18 10:15
Electronic Cleansing for CT Colonography using Deep Learning
Rie Tachibana (NIT, Oshima College), Janne J. Nappi, Toru Hironaka, Hiroyuki Yoshida (MGH/HMS) SIP2018-8 IE2018-8 PRMU2018-8 MI2018-8
Abstract (in Japanese) (See Japanese page) 
(in English) Although colonoscopy is considered as a standard procedure for colon cancer screening, CT colonography (CTC) has recently been widely accepted as an alternative to colonoscopy. Currently, however, CTC requires pre-examination cathartic bowel cleansing, which is a well-known barrier of patient adherence to colorectal cancer screening. In this study, we developed an electronic cleansing scheme based on deep learning for virtually removing residual feces and fluid tagged by an orally administered contrast agent in CTC images. In our scheme, a deep convolutional neural network was used to generate multi-material labeled images from cut-plane images extracted at multiple angles at each voxel of a CTC volume. Electronically cleansed CTC images are generated from the multi-material labeled images by keeping only the materials labeled as soft tissue and removing all of the other materials including tagged fecal materials. Preliminary results showed that our deep-learning based method was able to classify voxels of the CTC volumes to multi-material classes with high accuracy when increased number of angled cut-plane images are used, and thus, our scheme was able to accurately remove residual fecal materials from the CTC images.
Keyword (in Japanese) (See Japanese page) 
(in English) CT colonography / Electronic cleansing / Deep learning / / / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 36, MI2018-8, pp. 35-37, May 2018.
Paper # MI2018-8 
Date of Issue 2018-05-10 (SIP, IE, PRMU, MI) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
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 SIP2018-8 IE2018-8 PRMU2018-8 MI2018-8

Conference Information
Committee PRMU MI IE SIP  
Conference Date 2018-05-17 - 2018-05-18 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
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Paper Information
Registration To MI 
Conference Code 2018-05-PRMU-MI-IE-SIP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Electronic Cleansing for CT Colonography using Deep Learning 
Sub Title (in English)  
Keyword(1) CT colonography  
Keyword(2) Electronic cleansing  
Keyword(3) Deep learning  
1st Author's Name Rie Tachibana  
1st Author's Affiliation National Institute of Technology, Oshima College (NIT, Oshima College)
2nd Author's Name Janne J. Nappi  
2nd Author's Affiliation Massachusetts General Hospital/Harvard Medical School (MGH/HMS)
3rd Author's Name Toru Hironaka  
3rd Author's Affiliation Massachusetts General Hospital/Harvard Medical School (MGH/HMS)
4th Author's Name Hiroyuki Yoshida  
4th Author's Affiliation Massachusetts General Hospital/Harvard Medical School (MGH/HMS)
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Date Time 2018-05-18 10:15:00 
Presentation Time 30 
Registration for MI 
Paper # IEICE-SIP2018-8,IEICE-IE2018-8,IEICE-PRMU2018-8,IEICE-MI2018-8 
Volume (vol) IEICE-118 
Number (no) no.33(SIP), no.34(IE), no.35(PRMU), no.36(MI) 
Page pp.35-37 
#Pages IEICE-3 
Date of Issue IEICE-SIP-2018-05-10,IEICE-IE-2018-05-10,IEICE-PRMU-2018-05-10,IEICE-MI-2018-05-10 

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