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7/7/2020 2:50:54 PM | Browse: 687 | Download: 1219
Publication Name World Journal of Gastroenterology
Manuscript ID 54644
Country/Territory Japan
Received
2020-02-17 03:34
Peer-Review Started
2020-02-10 14:29
To Make the First Decision
Return for Revision
2020-03-15 03:54
Revised
2020-04-03 16:16
Second Decision
2020-06-17 09:24
Accepted by Journal Editor-in-Chief
Accepted by Company Editor-in-Chief
2020-06-17 20:52
Articles in Press
2020-06-17 20:52
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript
2020-06-28 08:07
Publish the Manuscript Online
2020-07-07 14:50
ISSN 1007-9327 (print) and 2219-2840 (online)
Open Access This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Copyright © The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved.
Article Reprints For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
Permissions For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
Publisher Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
Website http://www.wjgnet.com
Category Gastroenterology & Hepatology
Manuscript Type Retrospective Study
Article Title Chronic atrophic gastritis detection with a convolutional neural network considering stomach regions
Manuscript Source Unsolicited Manuscript
All Author List Misaki Kanai, Ren Togo, Takahiro Ogawa and Miki Haseyama
ORCID
Author(s) ORCID Number
Misaki Kanai http://orcid.org/0000-0002-2227-1819
Ren Togo http://orcid.org/0000-0002-4474-3995
Takahiro Ogawa http://orcid.org/0000-0001-5332-8112
Miki Haseyama http://orcid.org/0000-0003-1496-1761
Funding Agency and Grant Number
Funding Agency Grant Number
JSPS KAKENHI Grant JP17H01744
Corresponding Author Ren Togo, PhD, Academic Research, Education and Research Center for Mathematical and Data Science, Hokkaido University, N-12, W-7, Kita-ku, Sapporo 0600812, Hokkaido, Japan. togo@lmd.ist.hokudai.ac.jp
Key Words Gastric cancer risk; Chronic atrophic gastritis; Helicobacter pylori; Gastric X-ray images; Deep learning; Convolutional neural network; Computer-aided diagnosis
Core Tip To construct a computer-aided diagnosis system, a method to detect chronic atrophic gastritis from gastric X-ray images (GXIs) with a patch-based convolutional neural network is presented in this paper. The proposed method utilizes two GXI groups for training: a manual annotation group and an automatic annotation group. The manual annotation group consists of GXIs for which we manually annotate the stomach regions, and the automatic annotation group consists of GXIs for which we automatically estimate the stomach regions. By utilizing GXIs with the stomach regions for training, the proposed method enables chronic atrophic gastritis detection that automatically eliminates the negative effect of the outside regions.
Publish Date 2020-07-07 14:50
Citation Kanai M, Togo R, Ogawa T, Haseyama M. Chronic atrophic gastritis detection with a convolutional neural network considering stomach regions. World J Gastroenterol 2020; 26(25): 3650-3659
URL https://www.wjgnet.com/1007-9327/full/v26/i25/3650.htm
DOI https://dx.doi.org/10.3748/wjg.v26.i25.3650
Full Article (PDF) WJG-26-3650.pdf
Full Article (Word) WJG-26-3650.docx
Manuscript File 54644-Review.docx
Answering Reviewers 54644-Answering reviewers.pdf
Audio Core Tip 54644-Audio core tip.m4a
Biostatistics Review Certificate 54644-Biostatistics statement.pdf
Conflict-of-Interest Disclosure Form 54644-Conflict-of-interest statement.pdf
Copyright License Agreement 54644-Copyright license agreement.pdf
Approved Grant Application Form(s) or Funding Agency Copy of any Approval Document(s) 54644-Grant application form(s).pdf
Signed Informed Consent Form(s) or Document(s) 54644-Informed consent statement.pdf
Institutional Review Board Approval Form or Document 54644-Institutional review board statement.pdf
Non-Native Speakers of English Editing Certificate 54644-Language certificate.pdf
Peer-review Report 54644-Peer-review(s).pdf
Scientific Misconduct Check 54644-Scientific misconduct check.pdf
Scientific Editor Work List 54644-Scientific editor work list.pdf