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DME Detection using LBP Features

by Ruaa Adeeb Abdulmunem Al-falluji
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 148 - Number 8
Year of Publication: 2016
Authors: Ruaa Adeeb Abdulmunem Al-falluji
10.5120/ijca2016911259

Ruaa Adeeb Abdulmunem Al-falluji . DME Detection using LBP Features. International Journal of Computer Applications. 148, 8 ( Aug 2016), 44-48. DOI=10.5120/ijca2016911259

@article{ 10.5120/ijca2016911259,
author = { Ruaa Adeeb Abdulmunem Al-falluji },
title = { DME Detection using LBP Features },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2016 },
volume = { 148 },
number = { 8 },
month = { Aug },
year = { 2016 },
issn = { 0975-8887 },
pages = { 44-48 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume148/number8/25781-2016911259/ },
doi = { 10.5120/ijca2016911259 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:52:50.997016+05:30
%A Ruaa Adeeb Abdulmunem Al-falluji
%T DME Detection using LBP Features
%J International Journal of Computer Applications
%@ 0975-8887
%V 148
%N 8
%P 44-48
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A system for detecting Diabetic Macular Edema (DME) using Optical Coherence Tomography (OCT) volumes is presented. In preprocessing stage noise removal and flattening of scans is done which is followed by Local binary pattern feature extraction. The extracted features are then classified using linear support vector machine classifier. The proposed system achieved an specificity and sensitivity of 100% and 86.67% respectively.

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Index Terms

Computer Science
Information Sciences

Keywords

Diabetic Macular Edema Optical Coherence Tomography DME OCT LBP

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