Retinal Vessels Segmentation Techniques and Algorithms: A Survey
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Authors
Almotiri, Jasem
Elleithy, Khaled M.
Elleithy, Abdelrahman
Issue Date
2018-01-23
Type
Article
Language
en_US
Keywords
Retinal vessels segmentation , Fuzzy expert systems , Fuzzy c means , Machine learning , Adaptive thresholding , Mathematical morphology , Vessel tracking
Alternative Title
Abstract
Retinal vessels identification and localization aim to separate the different retinal vasculature structure tissues, either wide or narrow ones, from the fundus image background and other retinal anatomical structures such as optic disc, macula, and abnormal lesions. Retinal vessels identification studies are attracting more and more attention in recent years due to non-invasive fundus imaging and the crucial information contained in vasculature structure which is helpful for the detection and diagnosis of a variety of retinal pathologies included but not limited to: Diabetic Retinopathy (DR), glaucoma, hypertension, and Age-related Macular Degeneration (AMD). With the development of almost two decades, the innovative approaches applying computer-aided techniques for segmenting retinal vessels are becoming more and more crucial and coming closer to routine clinical applications. The purpose of this paper is to provide a comprehensive overview for retinal vessels segmentation techniques. Firstly, a brief introduction to retinal fundus photography and imaging modalities of retinal images is given. Then, the preprocessing operations and the state of the art methods of retinal vessels identification are introduced. Moreover, the evaluation and validation of the results of retinal vessels segmentation are discussed. Finally, an objective assessment is presented and future developments and trends are addressed for retinal vessels identification techniques.
Description
Citation
Almotiri, J.; Elleithy, K.; Elleithy, A. Retinal Vessels Segmentation Techniques and Algorithms: A Survey. Appl. Sci. 2018, 8, 155.
Publisher
MDPI