eprintid: 6109
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/61/09
datestamp: 2023-11-09 16:17:51
lastmod: 2023-11-09 16:17:51
status_changed: 2023-11-09 16:04:54
type: conference_item
metadata_visibility: show
creators_name: Awais, M.
creators_name: Walter, N.
creators_name: Faye, I.
creators_name: Saad, M.N.
creators_name: Ramanathan, A.
creators_name: Zain, R.M.
title: Analysis of auto-fluorescence images for automatic detection of abnormalities in oral cavity
ispublished: pub
keywords: Diagnosis; Fluorescence; Image analysis; Image segmentation, Automatic Detection; Contrast stretching; Detection and diagnosis; Fluorescence image; Malignant disease; Oral cancer; Oral cavity; Sensitivity and specificity, Image processing
note: cited By 4; Conference of 7th International Conference on Information Technology and Electrical Engineering, ICITEE 2015 ; Conference Date: 29 October 2015 Through 30 October 2015; Conference Code:119463
abstract: Oral Potential Malignant Disease (OPMD) is a growing and significant health problem all over the world. OPMDs have the potential to lead to oral cancer. The detection and diagnosis of these OPMDs in their early phases is a challenging task for clinicians. This paper focuses on the identification of OPMDs in visually enhanced lesion scope (VELscope) images using the contrast stretching technique. The parameters of the contrast stretching technique have been set automatically based on a statistical analysis of a set of images. The results show a better differentiation of OPMDs from the normal region. The proposed technique has shown a higher (greater than 90) accuracy, sensitivity and specificity. © 2015 IEEE.
date: 2015
publisher: Institute of Electrical and Electronics Engineers Inc.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84966495084&doi=10.1109%2fICITEED.2015.7408943&partnerID=40&md5=345218e1cacb832cf1c0b49013ec122f
id_number: 10.1109/ICITEED.2015.7408943
full_text_status: none
publication: Proceedings - 2015 7th International Conference on Information Technology and Electrical Engineering: Envisioning the Trend of Computer, Information and Engineering, ICITEE 2015
pagerange: 209-214
refereed: TRUE
isbn: 9781467378635
citation:   Awais, M. and Walter, N. and Faye, I. and Saad, M.N. and Ramanathan, A. and Zain, R.M.  (2015) Analysis of auto-fluorescence images for automatic detection of abnormalities in oral cavity.  In: UNSPECIFIED.