Abstract
Diabetic retinopathy has been found in from 22% of diabetic patients from the latest survey, which can lead to blindness later. Thus, eye exams should be scheduled no less than annually for patients with diabetes. On the other hand, there is an apparent deficiency in the number of medical professionals specializing in ophthalmology, which may hinder the discovery and care of diabetic retinopathy. The idea to stimulate a detection system for screening of diabetic retinopathy by using morphological and image segmentation methods to facilitate and make a preliminary decision with ophthalmologists is introduced. From the experimental results, the detection system provides good exudate detection and classification results for all 60 retina images for accurate up to 85%.
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Acknowledgements
This project is supported by Department of Computer Engineering, Faculty of Engineering, Mahidol University. We would like to thank Institute of Medical Research and Technology Assessment for the database.
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Tanthuwapathom, R., Hnoohom, N. (2018). Detection of Diabetic Retinopathy Using Image Processing. In: Theeramunkong, T., Kongkachandra, R., Supnithi, T. (eds) Advances in Natural Language Processing, Intelligent Informatics and Smart Technology. SNLP 2016. Advances in Intelligent Systems and Computing, vol 684. Springer, Cham. https://doi.org/10.1007/978-3-319-70016-8_22
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DOI: https://doi.org/10.1007/978-3-319-70016-8_22
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