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©The Author(s) 2016. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Oct 21, 2016; 22(39): 8641-8657
Published online Oct 21, 2016. doi: 10.3748/wjg.v22.i39.8641
Published online Oct 21, 2016. doi: 10.3748/wjg.v22.i39.8641
Potential of hybrid adaptive filtering in inflammatory lesion detection from capsule endoscopy images
Vasileios S Charisis, Leontios J Hadjileontiadis, Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, GR54124 Thessaloniki, Greece
Leontios J Hadjileontiadis, Department of Electrical and Computer Engineering, Khalifa University, Abu Dhabi, PO Box 127788, United Arab Emirates
Author contributions: Charisis VS designed the texture feature extraction procedure, namely DLac, and wrote the manuscript; Hadjileontiadis LJ designed the hybrid adaptive filtering procedure and made revisions to the manuscript.
Conflict-of-interest statement: No potential conflicts of interest relevant to this article were reported.
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: Leontios J Hadjileontiadis, PhD, Professor, Composer/Musicologist, Director of the Signal Processing and Biomedical Technology Unit (SPBTU), Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, University Campus, Build. D, 6th floor, GR54124 Thessaloniki, Greece. leontios@auth.gr
Telephone: +30-231-0996340 Fax: +30-231-0996312
Received: July 13, 2016
Peer-review started: July 16, 2016
First decision: August 19, 2016
Revised: September 2, 2016
Accepted: September 14, 2016
Article in press: September 14, 2016
Published online: October 21, 2016
Peer-review started: July 16, 2016
First decision: August 19, 2016
Revised: September 2, 2016
Accepted: September 14, 2016
Article in press: September 14, 2016
Published online: October 21, 2016
Core Tip
Core tip: This paper presents a novel procedure to analyze wireless capsule endoscopy (WCE) images and extract features towards the automatic detection of Crohn’s disease-based lesions. In this direction, a hybrid adaptive filtering process is proposed that aims to refine the WCE images, prior to feature extraction, by selecting via a genetic algorithm approach the most informative curvelet-based components of the images. Then, differential lacunarity is employed for extracting color-texture features in YCbCr color space. The experimental results showed that the proposed WCE image analysis scheme is robust and outperforms related approaches of the literature, mainly in the case of mild lesions detection.