Anomaly Detection System for Retinal Images Based on Area Classifier

Autor: Salah S. Elagooz, Mohamed A. M. Amer, Mohamed A. Abdelhamed, Walid El-Shafai, Ashraf A. M. Khalaf, Fathi E. Abd El-Samie, Noha A. El-Hag, Mohamed Rihan, Ghada M. El-Banby
Rok vydání: 2021
Předmět:
Zdroj: 2021 International Conference on Electronic Engineering (ICEEM).
DOI: 10.1109/iceem52022.2021.9480630
Popis: Diabetic Retinopathy (DR) is a disease of the eye for diabetics, and it can lead to a lack of vision if leaved untreated. The proposed approach in this paper is used to help for detecting and classifying the DR. It is applied to detect non-proliferative DR by identifying micro-aneurysms and hemorrhages. Firstly, the pre-processing step is applied. It consists of extracting the green channel, removing the optic disc (OD) and normalizing the background. Then, h-maxima transformation is performed. After that, threshold segmentation is applied to detect the hemorrhages and micro-aneurysms, accurately. Finally, an area classifier is used for the classification process to discriminate dark spot lesions.
Databáze: OpenAIRE