Abstract
This paper proposes an analysis and detection of diabetic retinopathy by using artificial vision technics, such as filtering, transforms, edge detection and segmentation on color fundus images to recognize and categorize microaneurysm, hemorrhages and exudates. The algorithms were validated with the DIARETDB database. Of the processed images are determined the descriptors for the design of two classifiers, the first based on vector support machines and the second with neural networks.
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Acknowledgment
The authors thank to IMAGERET project, Lappeenranta University of Technology, Finland for providing a public database for Diabetic retinopathy with experts ground truth marking.
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González, H., Arizmendi, C., Aza, J. (2021). Design of an Automatic System to Determine the Degree of Progression of Diabetic Retinopathy. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Systems and Applications. IntelliSys 2020. Advances in Intelligent Systems and Computing, vol 1251. Springer, Cham. https://doi.org/10.1007/978-3-030-55187-2_4
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DOI: https://doi.org/10.1007/978-3-030-55187-2_4
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