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.
Highlights
Retinal vasculature structure implicates important information helps the ophthalmologist in detecting and diagnosing a variety of retinal pathology such as Retinopathy of Prematurity (RoP), diabetic retinopathy, glaucoma, hypertension, and age-related macular degeneration or in diagnosis of diseases related to brain and heart stocks, which are associated with the abnormal variations in retinal vascular structure
We have presented a review that covers and categorizes early and recent literature methodologies and techniques, with the major focus on the detection and segmentation of retinal vasculature structures in two-dimensional retinal fundus images
Most retinal vessels segmentation methodologies are built based on the pyramid multi-scale type, where the grey-level data are represented in such a way that combines sampling operations with successive smoothing steps conducted by Gaussian kernels with different scales gives rise to a response that is represented by 2D Hessian matrix [106]
Summary
Retinal vasculature structure implicates important information helps the ophthalmologist in detecting and diagnosing a variety of retinal pathology such as Retinopathy of Prematurity (RoP), diabetic retinopathy, glaucoma, hypertension, and age-related macular degeneration or in diagnosis of diseases related to brain and heart stocks, which are associated with the abnormal variations in retinal vascular structure. Vessels (vessels structure-like) segmentation occupy a remarkable place in medical image segmentation field [1,2,3,4]; retinal vessels segmentation belongs to this category where a broad variety of algorithms and methodologies have been developed and implemented for the sake of automatic identification, localization and extraction of retinal vasculature structures [5,6,7,8,9,10]. We have presented a review that covers and categorizes early and recent literature methodologies and techniques, with the major focus on the detection and segmentation of retinal vasculature structures in two-dimensional retinal fundus images. Our review covers the theoretical basis behind each segmentation category as well as the associated advantages and limitations.
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