Klasifikasi Citra Glaukoma dengan ANN Berdasarkan Pembuluh Darah Pada Citra Fundus Retina Mengguna

Glaucoma is an eye disease that can lead to permanent blindness caused by increased Intraocular Pressure (IOP). There are several methods detect glaucoma, namely Optical Nerve Hypoplasia Stereo Photographs (ONHSPs), Coherence Tomography (OCT), Scanning Laser Polarimetry (SLP), and Confocal Ophthalmoscopy (CSLO). However, these require a lot of money expert supervision. In this paper, glaucoma classification will be carried out using the ANN method with comparison otsu-thresholding segmentation canny edge detection aim knowing which gives better results in diagnosing images based on parameters accuracy, sensitivity, specificity. The dataset used RIM-ONE r2 r3 extracted 5 features GLCM 6 statistical features, obtained accuracy 76% for method, 79% detection.