relation: https://khub.utp.edu.my/scholars/11423/
title: Bleeding detection in wireless capsule endoscopy videos � Color versus texture features
creator: Pogorelov, K.
creator: Suman, S.
creator: Azmadi Hussin, F.
creator: Saeed Malik, A.
creator: Ostroukhova, O.
creator: Riegler, M.
creator: Halvorsen, P.
creator: Hooi Ho, S.
creator: Goh, K.-L.
description: Wireless capsule endoscopy (WCE) is an effective technology that can be used to make a gastrointestinal (GI) tract diagnosis of various lesions and abnormalities. Due to a long time required to pass through the GI tract, the resulting WCE data stream contains a large number of frames which leads to a tedious job for clinical experts to perform a visual check of each and every frame of a complete patient�s video footage. In this paper, an automated technique for bleeding detection based on color and texture features is proposed. The approach combines the color information which is an essential feature for initial detection of frame with bleeding. Additionally, it uses the texture which plays an important role to extract more information from the lesion captured in the frames and allows the system to distinguish finely between borderline cases. The detection algorithm utilizes machine-learning-based classification methods, and it can efficiently distinguish between bleeding and nonbleeding frames and perform pixel-level segmentation of bleeding areas in WCE frames. The performed experimental studies demonstrate the performance of the proposed bleeding detection method in terms of detection accuracy, where we are at least as good as the state-of-the-art approaches. In this research, we have conducted a broad comparison of a number of different state-of-the-art features and classification methods that allows building an efficient and flexible WCE video processing system. © 2019 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.
publisher: John Wiley and Sons Ltd
date: 2019
type: Article
type: PeerReviewed
identifier:   Pogorelov, K. and Suman, S. and Azmadi Hussin, F. and Saeed Malik, A. and Ostroukhova, O. and Riegler, M. and Halvorsen, P. and Hooi Ho, S. and Goh, K.-L.  (2019) Bleeding detection in wireless capsule endoscopy videos � Color versus texture features.  Journal of Applied Clinical Medical Physics, 20 (8).  pp. 141-154.  ISSN 15269914     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070772272&doi=10.1002%2facm2.12662&partnerID=40&md5=08360578cb56f307ef5cd760922e316e
relation: 10.1002/acm2.12662
identifier: 10.1002/acm2.12662