Title: Segmentation of retinal features in colour fundus images

Authors: N. Bino; P.A. Haris; O. Sheeba

Addresses: Department of ECE, Bishop Jerome Institute, Kerala-691001, India ' Department of ECE, College of Engineering Trivandrum, Kerala-695016, India ' Department of ECE, T.K.M. College of Engineering, Kollam, Kerala-691013, India

Abstract: Retinal diseases could be diagnosed by the variations in size, shape and texture of features in retinal images. Colour fundus images are widely used for the diagnosis of retinal diseases like diabetic retinopathy (DR), glaucoma, age-related macular degeneration (AMD), etc. Image processing enhances the input image, which segments and highlights regions of interest and quantify it. In this paper, we have segmented optic disc and blood vessels in colour fundus images using an algorithm coded in MATLAB. The input images and their corresponding ground truth images were obtained from public datasets available in Kaggle. The validation of the segmented images is done for parameters like accuracy, sensitivity, precision, F-measure, Mathews correlation coefficient, Dice coefficient, Jaccard index and specificity. The algorithm could effectively segment images, with an average accuracy of 99.74% in segmenting optic disc and 94.74% that of blood vessels.

Keywords: retinal image segmentation; colour fundus imaging; optic disc; retinal blood vessels.

DOI: 10.1504/IJMEI.2025.147584

International Journal of Medical Engineering and Informatics, 2025 Vol.17 No.4, pp.333 - 345

Received: 21 Aug 2022
Accepted: 19 Nov 2022
Published online: 24 Jul 2025 *

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