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Survey on retinal vessel segmentation

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Abstract

The primary causes of vision loss are disorders of the retina, such as diabetic retinopathy (DR). The ability to segment blood vessels in retinal images is crucial for the early detection of eye disorders. The geometric characteristics of the ocular arteries can be used to distinguish between various ocular illnesses symptoms. However, segmenting the retina image is a difficult task because of the intricate structure of the blood vessels and their varying thicknesses. Many segmentation techniques have aided in the identification of retinal disorders. These segmentation approaches vary in complexity, from simple clustering algorithms to more complex machine-learning models. This research is essential to understand the contemporary segmentation methods and the challenges that still lay ahead. It also provides a useful overview of the current trends in retinal vascular segmentation, allowing researchers to identify potential areas for further development. By understanding the current trends, researchers can develop more effective segmentation techniques that are tailored to specific applications. Additionally, they can improve existing algorithms and methods, making them more accurate and efficient. By comparing different methods and algorithms on freely accessible databases, researchers can gain a greater comprehension of the strengths and weaknesses of each method. In order to provide a systematic review, articles from 2004 to 2023 are considered, with an emphasis on techniques based on segmenting and classifying retinal vessels utilizing fundus camera pictures.

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Authors and Affiliations

  1. Faculty of Integrated Technologies, Universiti Brunei Darussalam, Gadong, BE1410, Brunei

    Arunakranthi Godishala, Veena Raj & Hayati Yassin

  2. Institute of Applied Data Analytics (IADA), Universiti Brunei Darussalam, Gadong, BE1410, Brunei

    Daphne Teck Ching Lai & Hayati Yassin

  3. School of Digital Science, Universiti Brunei Darussalam, Gadong, BE1410, Brunei

    Daphne Teck Ching Lai

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  1. Arunakranthi Godishala
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  3. Daphne Teck Ching Lai
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  4. Hayati Yassin
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Correspondence to Hayati Yassin.

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Godishala, A., Raj, V., Lai, D.T.C. et al. Survey on retinal vessel segmentation. Multimed Tools Appl (2024). https://doi.org/10.1007/s11042-024-19075-1

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