Purpose To identify and quantify the three distinct retinal capillary plexuses and the foveal avascular zone (FAZ) in healthy subjects according to age using optical coherence tomography angiography (OCTA) with novel projection artifact removal (PAR) software and improved segmentation. Methods All eyes in this cross-sectional study underwent OCTA imaging using RTVue XR Avanti with novel PAR A...

Automated image processing has the potential to assist in the early detection of diabetes, by detecting changes in blood vessel diameter and patterns in the retina. This paper describes the development of segmentation methodology in the processing of retinal blood vessel images obtained using non-mydriatic colour photography. The methods used include wavelet analysis, supervised classifier prob...

Computerized segmentation of retinal vessels can help doctors discover diabetic retinopathy, Retinal Tear and Detachment. Because the anatomy is complicated changing, automated vessel still a difficult task. The Expectation-Maximization approach for vascular proposed in this paper, which uses matched filter (MF) that combines Mask based Blood Vessels Extraction with global image threshold to ex...

The change in morphology, diameter, branching pattern and/or tortuosity of retinal blood vessels is an important indicator of various clinical disorders of the eye and the body. This paper reports an automated method for segmentation of blood vessels in retinal images by means of a unique combination of differential filtering and morphological processing. The centerlines are extracted by the ap...

• Recent vessel segmentation using machine and deep learning methods are reviewed. Performance of non-deep evaluated. An artery/vein classification Summary tables presented, reporting key algorithms, validation databases, challenges addressed. The eye affords a unique opportunity to inspect rich part the human microvasculature non-invasively via retinal imaging. Retinal blood prime steps for di...

In this article, we propose a new method for localizing optic disc in retinal images. Localizing the optic disc and its center is the first step of most vessel segmentation, disease diagnostic, and retinal recognition algorithms. We use optic disc of the first four retinal images in DRIVE dataset to extract the histograms of each color component. Then, we calculate the average of histograms for...

Diabetic Retinopathy (DR) is a very rigorous and extensive eye disease which causes blindness in diabetic patients. DR primary cause for blindness is not for the reason that it has the highest occurrence but it often remains unobserved until severe vision loss occurs. Diabetic Retinopathy is characterized by changes in the retina that comprise of change in blood vessel diameter, micro aneurysms...

Diabetic Retinopathy (DR) is the leading ophthalmic pathological reason of blindness among people of working age in developed countries. The main cause of DR is abnormal blood glucose level rise, which damages vessel endothelium, causing an increase in the vessel permeability. The initial manifestations of DR are tiny capillary dilations known as microaneurysms. A method for automatic detection...

Digital image analysis of eye fundus images has several benefits than current observer based techniques. The characteristic symptoms of different systemic diseases like hypertension, glaucoma, diabetes and cardiovascular disorder etc. affects retinal vessels. Diseases like diabetes show abnormalities and diameter changes in retinal blood vessels. In hypertension retinal blood vessels show dilat...

With the advancement of CAD (Computer Assisted Diagnosis) Image Processing in Medical Field has created its own niche. Retinal Blood Vessels are highly complicated with low contrast and of very thin diameter which often causes failure in diagnosis of exact abnormalities. However, many researchers have worked on enhancement and segmentation of Retinal Blood Vessels through various methods over t...