Voting Based Automatic Exudate Detection in Color Fundus Photographs (CROSBI ID 614119)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Prentašić, Pavle ; Lončarić, Sven
engleski
Voting Based Automatic Exudate Detection in Color Fundus Photographs
Diabetic retinopathy is one of the leading causes of preventable blindness. Screening programs using color fundus photographs enable early diagnosis of diabetic retinopathy, which enables timely treatment of the disease. Exudate detection algorithms are important for development of automatic screening systems and in this paper we present a method for detection of exudate regions in color fundus photographs. The method combines different preprocessing and candidate extraction algorithms to increase the exudate detection accuracy. First, we form an ensemble of different candidate extraction algorithms, which are used to increase the accuracy. After extracting the potential exudate regions we apply machine learning based classification for detection of exudate regions. For experimental validation we use the DRiDB color fundus image set where the presented method achieves higher accuracy in comparison to other state-of-the art methods.
diabetic retinopathy; exudate detection; machine learning; ensemble; image processing and analysis
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Podaci o prilogu
2014.
objavljeno
Podaci o matičnoj publikaciji
Proceedings of the 22nd European Signal Processing Conference 2014
Podaci o skupu
22nd Europen Signal Processing Conference (EUSIPCO)
predavanje
01.09.2014-05.09.2014
Lisabon, Portugal