Ratikanlaya TanthuwapathomNarit HnoohomMahidol University2019-08-232019-08-232018-01-01Advances in Intelligent Systems and Computing. Vol.684, (2018), 259-265219453572-s2.0-85044421629https://repository.li.mahidol.ac.th/handle/20.500.14594/45668© Springer International Publishing AG 2018. 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%.Mahidol UniversityComputer ScienceEngineeringConference PaperSCOPUS10.1007/978-3-319-70016-8_22