An Approach to Automatic Hard Exudate Detection in Retina Color Images by a Telemedicine System Based on the d-Eye Sensor and Image Processing Algorithms

Emil Saeed , Maciej Szymkowski , Khalid Saeed , Zofia Mariak

Abstract

Hard exudates are one of the most characteristic and dangerous signs of diabetic retinopathy. They can be marked during the routine ophthalmological examination and seen in color fundus photographs (i.e., using a fundus camera). The purpose of this paper is to introduce an algorithm that can extract pathological changes (i.e., hard exudates) in diabetic retinopathy. This was a retrospective, nonrandomized study. A total of 100 photos were included in the analysis—50 sick and 50 normal eyes. Small lesions in diabetic retinopathy could be automatically diagnosed by the system with an accuracy of 98%. During the experiments, the authors used classical image processing methods such as binarization or median filtration, and data was read from the d-Eye sensor. Sixty-seven patients (39 females and 28 males with ages ranging between 50 and 64) were examined. The results have shown that the proposed solution accuracy level equals 98%. Moreover, the algorithm returns correct classification decisions for high quality images and low quality samples. Furthermore, we consider taking retina photos using mobile phones rather than fundus cameras, which is more practical. The paper presents an innovative approach. The results are introduced and the algorithm is described.
Author Emil Saeed
Emil Saeed,,
-
, Maciej Szymkowski (FCS / DDMCG)
Maciej Szymkowski,,
- Department of Digital Media and Computer Graphics
, Khalid Saeed (FCS / DDMCG)
Khalid Saeed,,
- Department of Digital Media and Computer Graphics
, Zofia Mariak
Zofia Mariak,,
-
Journal seriesSensors, [SENSORS-BASEL], ISSN 1424-8220, (N/A 100 pkt)
Issue year2019
Vol19
No3
Pages1-18
Publication size in sheets0.85
ASJC Classification1303 Biochemistry; 1602 Analytical Chemistry; 2208 Electrical and Electronic Engineering; 3107 Atomic and Molecular Physics, and Optics
DOIDOI:10.3390/s19030695
URL https://www.mdpi.com/1424-8220/19/3/695/pdf/1
Internal identifier000044899
Languageen angielski
LicenseJournal (articles only); published final; Uznanie Autorstwa (CC-BY); with publication
Score (nominal)100
Score sourcejournalList
ScoreBUT score = 36.0, 31-05-2019, manual
Ministerial score = 100.0, 09-03-2020, ArticleFromJournal
Publication indicators Scopus SNIP (Source Normalised Impact per Paper): 2016 = 1.393; WoS Impact Factor: 2018 = 3.031 (2) - 2018=3.302 (5)
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