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Automatic detection of microaneurysms in colour fundus images for diabetic retinopathy screening

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Abstract

Regular eye screening is essential for the early detection and treatment of the diabetic retinopathy. This paper presents a novel automatic screening system for diabetic retinopathy that focuses on the detection of the earliest visible signs of retinopathy, which are microaneurysms. Microaneurysms are small dots on the retina, formed by ballooning out of a weak part of the capillary wall. The detection of the microaneurysms at an early stage is vital, and it is the first step in preventing the diabetic retinopathy. The paper first explores the existing systems and applications related to diabetic retinopathy screening, with a focus on the microaneurysm detection methods. The proposed decision support system consists of an automatic acquisition, screening and classification of diabetic retinopathy colour fundus images, which could assist in the detection and management of the diabetic retinopathy. Several feature extraction methods and the circular Hough transform have been employed in the proposed microaneurysm detection system, alongside the fuzzy histogram equalisation method. The latter method has been applied in the preprocessing stage of the diabetic retinopathy eye fundus images and provided improved results for detecting the microaneurysms.

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Acknowledgments

This project is a part of Ph.D. research currently being carried out at the Faculty of Engineering and Computing, Coventry University, UK. The deepest gratitude and thanks go to the Universiti Teknikal Malaysia Melaka (UTeM) and Ministry of Education Malaysia for sponsoring this Ph.D. research.

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Authors and Affiliations

  1. Faculty of Engineering and Computing, Coventry University, Priory Street, Coventry, CV1 5FB, UK

    Sarni Suhaila Rahim, Chrisina Jayne, Vasile Palade & James Shuttleworth

  2. Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100, Durian Tunggal, Melaka, Malaysia

    Sarni Suhaila Rahim

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  1. Sarni Suhaila Rahim
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Correspondence to Sarni Suhaila Rahim.

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Rahim, S.S., Jayne, C., Palade, V. et al. Automatic detection of microaneurysms in colour fundus images for diabetic retinopathy screening. Neural Comput & Applic 27, 1149–1164 (2016). https://doi.org/10.1007/s00521-015-1929-5

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