Open Access

ARTICLE

QI-BRiCE: Quality Index for Bleeding Regions in Capsule Endoscopy Videos

Muhammad Arslan Usman¹, Muhammad Rehan Usman², Gandeva Bayu Satrya³, Muhammad Ashfaq Khan⁴, Christos Politis¹, Nada Philip¹, Soo Young Shin^5,*
1 Faculty of Science, Engineering and Computing, Kingston University, London, KT1 2EE, UK
2 School of Electrical Engineering, Superior University, Lahore, Pakistan
3 School of Applied Sciences, Telkom University, Bandung, Indonesia
4 Department of Network Computing, System Architecture Lab, Dongguk University, Seoul, Korea
5 Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, Korea
* Corresponding Author: Soo Young Shin. Email:
(This article belongs to this Special Issue: Machine Learning-based Intelligent Systems: Theories, Algorithms, and Applications)

Computers, Materials & Continua 2021, 67(2), 1697-1712. https://doi.org/10.32604/cmc.2021.014696

Received 09 October 2020; Accepted 05 December 2020; Issue published 05 February 2021

Abstract

With the advent in services such as telemedicine and telesurgery, provision of continuous quality monitoring for these services has become a challenge for the network operators. Quality standards for provision of such services are application specific as medical imagery is quite different than general purpose images and videos. This paper presents a novel full reference objective video quality metric that focuses on estimating the quality of wireless capsule endoscopy (WCE) videos containing bleeding regions. Bleeding regions in gastrointestinal tract have been focused in this research, as bleeding is one of the major reasons behind several diseases within the tract. The method jointly estimates the diagnostic as well as perceptual quality of WCE videos, and accurately predicts the quality, which is in high correlation with the subjective differential mean opinion scores (DMOS). The proposed combines motion quality estimates, bleeding regions’ quality estimates based on support vector machine (SVM) and perceptual quality estimates using the pristine and impaired WCE videos. Our method Quality Index for Bleeding Regions in Capsule Endoscopy (QI-BRiCE) videos is one of its kind and the results show high correlation in terms of Pearsons linear correlation coefficient (PLCC) and Spearman’s rank order correlation coefficient (SROCC). An F-test is also provided in the results section to prove the statistical significance of our proposed method.

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Keywords

Automated bleeding detection; high efficiency video coding; video quality assessment; wireless capsule endoscopy

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