Erwin, Erwin (2020) Techniques for Exudate Detection for Diabetic Retinopathy. In: 2019 International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS), 24-25 Oct 2019, Jakarta.
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Abstract
Diabetic Retinopathy (DR) is an eye disease caused by diabetic complications that have early signs of a disease containing microaneurysms and exudates. Diabetic retinopathy for a long time can cause vision loss (blindness). So automatic detection is needed. Therefore we conduct research for the detection of exudates based on segmentation using the STARE and DIARETDB1 datasets. The exudate appears yellowish and glowing in the background of the retina with irregular size and shape. The use of several segmentation methods can be done in exudate detection. The method used is the adaptive threshold method, multi-threshold otsu, top-hat and bottom hat, and fuzzy c-means performance. The average performance results of several methods used in segmenting for each image in the STARE dataset are otsu multi threshold 87.1%, adaptived threshold of 89.9%, top-hat and bottom hat 87.7% and fuzzy cmeans 95.4%. and in the DIARETDB1 dataset, otsu multi threshold is 89%, adaptive threshold is 88.2%, top-hat and bottom hat 92.9% and fuzzy c-means 90.6%. These results indicate that the proposed method can provide good exudate segmentation results.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation. |
| Divisions: | 09-Faculty of Computer Science > 56201-Computer Systems (S1) |
| Depositing User: | Dr Erwin Erwin |
| Date Deposited: | 12 Oct 2020 00:43 |
| Last Modified: | 12 Oct 2020 00:43 |
| URI: | http://repository.unsri.ac.id/id/eprint/36523 |
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Techniques for Exudate Detection for Diabetic Retinopathy. (deposited 20 Apr 2020 01:05)
- Techniques for Exudate Detection for Diabetic Retinopathy. (deposited 12 Oct 2020 00:43) [Currently Displayed]
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