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Articles Published Processes
7/7/2020 2:50:54 PM | Browse: 1291 | Download: 2608
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Received |
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2020-02-17 03:34 |
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Peer-Review Started |
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2020-02-10 14:29 |
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First Decision by Editorial Office Director |
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2020-03-15 03:54 |
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Return for Revision |
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2020-03-15 03:54 |
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Revised |
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2020-04-03 16:16 |
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Publication Fee Transferred |
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Second Decision by Editor |
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2020-06-17 09:24 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2020-06-17 20:52 |
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Articles in Press |
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2020-06-17 20:52 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2020-06-28 08:07 |
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Publish the Manuscript Online |
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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
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| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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| 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
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| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Misaki Kanai, Ren Togo, Takahiro Ogawa and Miki Haseyama |
| ORCID |
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| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| JSPS KAKENHI Grant |
JP17H01744 |
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| 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
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| URL |
https://www.wjgnet.com/1007-9327/full/v26/i25/3650.htm |
| DOI |
https://dx.doi.org/10.3748/wjg.v26.i25.3650 |
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