Abstract
Hard exudates are usually seen in the course of diabetic retinopathy. This illness is one of the most common reasons for blind registration in the world. Due to the data presented by World Health Organization (WHO) the number of people who lose sight because of undetected diabetes will be doubled by 2050. The purpose of this paper is to introduce an enhanced algorithm for hard exudates detection in Optical Coherence Tomography images. In these samples, dangerous pathological changes can be observed in the form of yellow-red spots. During the experiments more than 150 images were used to calculate the accuracy of the proposed approach. We created an algorithm that was implemented in development environment with Java Programming Language and Maven Framework. Classification was done on the basis of authors’ own algorithm results and compared with ophthalmologist decision. The experiments have shown the proposed approach has 97% of accuracy in hard exudates detection.
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Acknowledgments
This work was supported by grant S/WI/3/2018 from Białystok University of Technology and funded with resources for research by the Ministry of Science and Higher Education in Poland.
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Szymkowski, M., Saeed, E., Saeed, K., Mariak, Z. (2019). A Simple Algorithm for Hard Exudate Detection in Diabetic Retinopathy Using Spectral-Domain Optical Coherence Tomography. In: Gavrilova, M., Chang, J., Thalmann, N., Hitzer, E., Ishikawa, H. (eds) Advances in Computer Graphics. CGI 2019. Lecture Notes in Computer Science(), vol 11542. Springer, Cham. https://doi.org/10.1007/978-3-030-22514-8_15
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DOI: https://doi.org/10.1007/978-3-030-22514-8_15
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