UNIVERSITAS BINA DARMA, UNIVERSITAS BINA DARMA (2022) Diabetic Retinopathy Stages Classification Using 3D-GLCM. Diabetic Retinopathy Stages Classification Using 3D-GLCM.
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16. Rocky Yefrenes Dillak1, Sri Andayani2.pdf Download (197kB) | Preview |
Abstract
Sustainable Diabetic Mellitus may lead to several complications towards patients. One of the complications is diabetic retinopathy. Diabetic retinopathy is the type of complication towards the retinal and interferes with patients sight. Medical exami�nation toward patients with diabetic retinopathy is observed directly through retinal images using fundus camera. Diabetic retinopathy is classified into four classes based on severity, which are: normal, non-proliferative diabetic retinopathy (NPDR), pro�liferative diabetic retinopathy (PDR), and macular edema (ME). The aim of this research is to develop a method which can be used to classify the level of severity of diabetic retinopathy based on patients retinal images. Seven texture features were extracted from retinal images using gray level co-occurence matrix three dimension method (3D-GLCM). These features are maximum probability, correlation, contrast, energy, homogeneity, and entropy; subsequently trained using Levenberg-Marqurdt Backpropagation Neural Network (LMBP). This study used 600 data of patients retinal images, consist of 450 data retinal images for training and 150 data retinal images for testing. Based on the result of this test, the method can classify the sever�ity of diabetic retinopathy with sensitivity of 97.37%, specificity of 75% and accuracy of 91.67%.
| Item Type: | Article |
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| Subjects: | H Social Sciences > H Social Sciences (General) |
| Divisions: | Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science |
| Depositing User: | Mr Edi Surya Negara |
| Date Deposited: | 05 Jul 2022 04:36 |
| Last Modified: | 05 Jul 2022 04:36 |
| URI: | http://eprints.binadarma.ac.id/id/eprint/17161 |
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