eprintid: 8597
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/85/97
datestamp: 2023-11-09 16:20:30
lastmod: 2023-11-09 16:20:30
status_changed: 2023-11-09 16:13:02
type: conference_item
metadata_visibility: show
creators_name: Suman, S.
creators_name: Hussin, F.A.B.
creators_name: Malik, A.S.
creators_name: Pogorelov, K.
creators_name: Riegler, M.
creators_name: Ho, S.H.
creators_name: Hilmi, I.
creators_name: Goh, K.L.
title: Detection and classification of bleeding region in WCE images using color feature
ispublished: pub
keywords: Color; Endoscopy; Image classification; Indexing (of information); Support vector machines, Bleeding detections; Color features; Efficient technology; Experimental evaluation; Gastrointestinal tract; Important features; Sensitivity and specificity; Wireless capsule endoscopy, Feature extraction
note: cited By 16; Conference of 15th International Workshop on Content-Based Multimedia Indexing, CBMI 2017 ; Conference Date: 19 June 2017 Through 21 June 2017; Conference Code:130150
abstract: Wireless capsule endoscopy (WCE) is a modern and efficient technology to diagnose complete gastrointestinal tract (GIT) for various abnormalities. Due to long recording time of WCE, it acquires a huge amount of images, which is very tedious for clinical expertise to inspect each and every frame of a complete video footage. In this paper, an automated color feature based technique of bleeding detection is proposed. In case of bleeding, color is a very important feature for an efficient information extraction. Our algorithm is based on statistical color feature analysis and we use support vector machine (SVM) to classify WCE video frames into bleeding and non-bleeding classes with a high processing speed. An experimental evaluation shows that our method has promising bleeding detection performance with sensitivity and specificity higher than existing approaches. © 2017 Copyright is held by the owner/author(s).
date: 2017
publisher: Association for Computing Machinery
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85030756852&doi=10.1145%2f3095713.3095731&partnerID=40&md5=2c3231a30767ccaa894450a682df0adc
id_number: 10.1145/3095713.3095731
full_text_status: none
publication: ACM International Conference Proceeding Series
volume: Part F
refereed: TRUE
isbn: 9781450353335
citation:   Suman, S. and Hussin, F.A.B. and Malik, A.S. and Pogorelov, K. and Riegler, M. and Ho, S.H. and Hilmi, I. and Goh, K.L.  (2017) Detection and classification of bleeding region in WCE images using color feature.  In: UNSPECIFIED.