Naslov
Weighted Ensemble Based Automatic Detection of Exudates in Fundus Photographs

Autori
Prentašić, Pavle ; Lončarić, Sven

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of the 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society / - , 2014, 138-141

Skup
36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

Mjesto i datum
Chicago (IL), Sjedinjene Američke Države, 26.08.2014. - 30.08.2014

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
diabetic retinopathy; exudate detection; machine learning; image processing and analysis

Sažetak
Diabetic retinopathy (DR) is a visual complication of diabetes, which has become one of the leading causes of preventable blindness in the world. Exudate detection is an important problem in automatic screening systems for detection of diabetic retinopathy using color fundus photographs. In this paper, we present a method for detection of exudates in color fundus photographs, which combines several preprocessing and candidate extraction algorithms to increase the exudate detection accuracy. The first stage of the method consists of an ensemble of several exudate candidate extraction algorithms. In the learning phase, simulated annealing is used to determine weights for combining the results of the ensemble candidate extraction algorithms. The second stage of the method uses a machine learning-based classification for detection of exudate regions. The experimental validation was performed using the DRiDB color fundus image set. The validation has demonstrated that the proposed method achieved higher accuracy in comparison to state-of-the art methods.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

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