Title: A new segmentation method for retinal pathologies detection in optical coherence tomography images

Authors: Ben Khelfallah Amel; Messadi Mahammed; Lazouni Mohammed El Amine

Addresses: Department of Biomedical Engineering, Technology Faculty, Biomedical Laboratory, University of Tlemcen 13000, Algeria ' Department of Biomedical Engineering, Technology Faculty, Biomedical Laboratory, University of Tlemcen 13000, Algeria ' Department of Biomedical Engineering, Technology Faculty, Biomedical Laboratory, University of Tlemcen 13000, Algeria

Abstract: Diabetic macular oedema (DME) and age-related macular degeneration (AMD) are the leading causes of blindness in adults. The most significant signs of these diseases are appearance of exudates and change of retinal layer structure. Screening of these diseases is very important to prevent vision loss. In this work, a new method based on a genetic k-means algorithm for lesions detection is proposed. From the selected region of interest (ROI), four textural features are extracted and used to classify these two retinal diseases against the normal subjects using the SD-OCT images. From the experimental results found, the SVM gives better results for AMD and DME recognition. The mean accuracy, sensitivity and specificity values for the macular region's classification are 99.67%, 100% and 99.51% respectively.

Keywords: OCT images; age-related macular degeneration; AMD; diabetic macular oedema; DME; features extraction; classification; genetic algorithms.

DOI: 10.1504/IJMEI.2024.135687

International Journal of Medical Engineering and Informatics, 2024 Vol.16 No.1, pp.34 - 46

Published online: 22 Dec 2023 *