Deteksi Penyakit Diabetes Retinopati Pada Retina Mata Berdasarkan Pengolahan Citra
Abstract: Diabetic Retinopathy
is a disease that strikes the retina of the eye in patients who have diabetes
mellitus. Medical examination against sufferers of Diabetic Retinopathy is done
with observation directly by eye surgeons. In this case, eye retinal images are
taken using the camera the fundus. Retinal fundus Photographs resulted from
fundus cameras usually are not able to give a clear picture against the retinal
blood vessels. This makes it difficult for doctor to analyze images of the
retina. It takes a relatively long time to find out the results of the
examination. Overcoming these weaknesses, a system was built using a
computational model to change the retina image pixel retina into a feature of
the retina. So it can help the doctor to decide medical actions quickly and
precisely. In this research a system that can detect and classify the diabetic
retinopathy was created, using local binary pattern method to extract the
characteristics and learning vector quantization method for the classification
process. Local binary pattern will generate an image of a uniform which has the
most image information. The image will be a characteristics vector as input to
the method of classification learning vector quantization. The results of the
testing show that the number of levels of extraction of characteristics affect
the results of the classification, in this case the best accuracy results is
85%.
Keywords: Diabetic
Retinopathy, Fundus Image, Local Binary Pattern, Pre-Processing, Learning
Vector Quantization
Penulis: Adri Pramana Putra
Putra, Youllia Indrawaty Nurhasanah, Andriana Zulkarnain
Kode Jurnal: jptinformatikadd170219
