| Yazarlar |
Doç. Dr. Kemal AKYOL
Kastamonu Üniversitesi, Türkiye |
Baha Şen
Ankara Yıldırım Beyazıt Üniversitesi, Türkiye |
| Özet |
| Detection of the optic disc which has similar brightness with the hard and soft exudate lesions seen in the early stage of diabetic retinopathy is very difficult due to different light conditions and contrast values. Automatic detection of these lesions by expert systems in the medical field is very important. In this context, we propose a new approach based on the analysis of color spaces, keypoint detectors, and texture for retinal fundus images. If the keypoint information is contained within the actual optic disc region, this is an important consideration for the automated detection of the optic disc. This study can be divided into five sections, respectively, image preprocessing, image processing, keypoint detection, texture analysis, and performance evaluation. The analyses of patch images compatible with the keypoints obtained from the Red–Green–Blue (RGB) image and its color channels were carried out. The performance of the study was validated on the Digital Retinal Images for Vessel Extraction public dataset. According to the results, Local Binary Pattern texture analysis performed in region of interest around keypoints detected by different keypoint detectors presented good performance in RGB and green channel images. |
| Anahtar Kelimeler |
| Error distance | Jaccard index | Keypoint detection | Optic disc | Texture analysis |
| Makale Türü | Özgün Makale |
| Makale Alt Türü | ESCI dergilerinde yayımlanan tam makale |
| Dergi Adı | SN APPLIED SCIENCES |
| Dergi ISSN | 2523-3963 |
| Dergi Tarandığı Indeksler | Web of Science - Emerging Sources Citation Index |
| Makale Dili | Türkçe |
| Basım Tarihi | 09-2021 |
| Cilt No | 3 |
| Sayı | 9 |
| Doi Numarası | 10.1007/s42452-021-04754-7 |
| Makale Linki | 10.1007/s42452-021-04754-7 |
| Atıf Sayıları | |
| SCOPUS | 2 |
