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©The Author(s) 2016. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Aug 21, 2016; 22(31): 7124-7134
Published online Aug 21, 2016. doi: 10.3748/wjg.v22.i31.7124
Published online Aug 21, 2016. doi: 10.3748/wjg.v22.i31.7124
Computer-aided texture analysis combined with experts' knowledge: Improving endoscopic celiac disease diagnosis
Michael Gadermayr, Dorit Merhof, Institute of Imaging and Computer Vision, RWTH Aachen University, D-52074 Aachen, Germany
Hubert Kogler, Maximilian Karla, Andreas Vécsei, Department of Pediatrics, Pediatric Gastroenterology, St, Anna Children’s Hospital, Medical University Vienna, A-1090 Vienna, Austria
Andreas Uhl, Department of Computer Sciences, University of Salzburg, A-5020 Salzburg, Austria
Author contributions: Gadermayr M and Kogler H contributed equally to this work; Gadermayr M, Kogler H, Karla M and Vécsei A jointly wrote the first draft of the manuscript; Furthermore, Gadermayr M, Kogler H, Uhl A and Vécsei A developed the study design and the concept; Gadermayr M and Uhl A developed the statistical analysis plan, interpreted the data, did the statistical analysis; Kogler H, Uhl A and Vécsei A participated in data collection; Uhl A and Vécsei A obtained the funding; Vécsei A supervised the study; all authors revised the manuscript for important intellectual content, read and approved the final manuscript.
Supported by the Austrian Science Fund (FWF) , No. KLI 429-B13 to Vécsei A.
Institutional review board statement: The study was reviewed and approved by the Institutional Review Board of the St. Anna Children’s Hospital.
Conflict-of-interest statement: Gadermayr M and Karla M have received research funding of the Austrian Science Fund (FWF). Kogler H, Merhof D, Uhl A and Vécsei A have no financial or other conflict of interest relevant to the subject of this article.
Data sharing statement: Statistical code is available from the corresponding author at michael.gadermayr@lfb.rwth-aachen.de. Participants gave informed consent for data sharing.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (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/
Correspondence to: Michael Gadermayr, PhD, Institute of Imaging and Computer Vision, RWTH Aachen University, Kopernikusstraße 16, D-52074 Aachen, Germany. michael.gadermayr@lfb.rwth-aachen.de
Telephone: +49-241-8022906 Fax: +49-241-8022200
Received: March 15, 2016
Peer-review started: March 18, 2016
First decision: March 31, 2016
Revised: April 28, 2016
Accepted: May 21, 2016
Article in press: May 23, 2016
Published online: August 21, 2016
Processing time: 152 Days and 18 Hours
Peer-review started: March 18, 2016
First decision: March 31, 2016
Revised: April 28, 2016
Accepted: May 21, 2016
Article in press: May 23, 2016
Published online: August 21, 2016
Processing time: 152 Days and 18 Hours
Core Tip
Core tip: A hybrid system for the detection of villous atrophy integrating human texture recognition into computer-aided diagnosis systems outperforms human judgement alone in the diagnosis of pediatric celiac disease. In the classification of 2835 endoscopic images from the duodenum into one of two categories (“normal mucosa or villous atrophy”) using 27 different classification settings the hybrid system was superior to human experts in 24 settings. This superiority was significant in 17 of these 24 settings. Less experienced endoscopists in particular can benefit from this new method because their diagnostic accuracy can be improved the most.