Fractal dimension and lacunarity analysis of retinal microvascular morphology in hypertension and diabetes. Arteriole-to-venule ratio, tortuosity index, and mean fractal dimension were altered in the subjects with hypertensive retinopathy or CADASIL with respect to age- and gender-matched controls.

Join ResearchGate to find the people and research you need to help your work. These methods are applied on the publicly available DRIVE database and the experimental results obtained by using green channel images have been presented and their results are compared with recently published methods. Hypertensive Retinopathy (HTR) is a disease caused by high blood pressure flowing into the retinal blood vessels, resulting in thickening of blood vessel walls and reducing blood flow in the retina. Moreover, the proposed method shows a better performance than comparative methods, such as the threshold for a Frangi filter, Adaptive Threshold, and multiple classes Otsu method. The results demonstrate that our algorithms are very effective methods to detect retinal blood vessels. Automated Retinal Blood Vessel Segmentation Using Fuzzy Mathematical Morphology and Morphological Re... Multilevel and Multiscale Deep Neural Network for Retinal Blood Vessel Segmentation, Two Novel Retinal Blood Vessel Segmentation Algorithms, Retinal blood vessel segmentation using curvelet transform and morphological reconstruction. HHS If you have diabetes, you may get a condition called diabetic retinopathy. Find NCBI SARS-CoV-2 literature, sequence, and clinical content: https://www.ncbi.nlm.nih.gov/sars-cov-2/. The algorithm for exudate recognition was applied to 30 retinal images of which 21 contained exudates and nine were without pathology. Our method uses a novel algorithm we call fuzzy convergence to determine the origination of the blood vessel network. Most of the cases can be prevented if detected in the early stages. WebMD does not provide medical advice, diagnosis or treatment.

To solve these problems, a novel hypertensive retinopathy (DenseHyper) system is developed to detect the HR based on a proposed trained features layer (TF-L) and dense feature transform layer (DFT-L) to the deep residual learning (DRL) methods.

In comparison with two published solution schemes that were also based on the STARE database, our scheme has lower FPR for the reported TPR measure. DenseHyper: an automatic recognition system for detection of hypertensive retinopathy using dense features transform and deep-residual learning, Assessment of Early Hypertensive Retinopathy using Fractal Analysis of Retinal Fundus Image, A novel methodology for vessel extraction from retinal fundus image and detection of neovascularization, Algorithmic Analysis of Vesselness and Blobness for Detecting Retinopathies Based on Fractional Gaussian Filters, Blood vessel segmentation in retinal fundus images using Gabor filters, fractional derivatives, and Expectation Maximization, Blood Vessel Segmentation on Retinal Fundus Image- A Review, The review of computer aided diagnostic hypertensive retinopathy based on the retinal image processing, Artery and Vein classification for hypertensive retinopathy, Detection of hypertensive retinopathy using principal component analysis (PCA) and backpropagation neural network methods, Decision support system for detection of hypertensive retinopathy using arteriovenous ratio, A divide et impera strategy for automatic classification of retinal vessels into arteries and veins, Automated localization of the optic disc, fovea and retinal blood vessels from digital color fundus images, Locating the optic nerve in a retinal image using the fuzzy convergence of the blood vessels, Measurement of Retinal Vessel Widths From Fundus Images Based on 2-D Modeling, Theoretical relations between light streak characteristics and optical properties of retinal vessels, A fuzzy vessel tracing algorithm for retinal images based on fuzzy clustering, Automated detection of diabetic retinopathy on digital fundus images, On the Adaptive Detection of Blood Vessels in Retinal Images, An improved matched filter for blood vessel detection of digital retinal images, Retinal Blood Vessel Segmentation Using Line Operators and Support Vector Classification. Hypertensive retinopathy is commonly considered a diagnostic feature of a hypertensive emergency although it is not invariably present. TI values were higher than control in the hypertensive retinopathy (P < 0.05) and CADASIL (P = 0.08 The acute effects of systemic arterial hypertension are a result of vasospasm to autoregulate perfusion. The performance is produced when using lacunarity the box size 2². Literature witness that most of the existing works emphasised on detecting only NVD. The proposed method was assessed using the public DRIVE database, for the Test image set and the 1st manual delineations. Vessel extraction from the retinal fundus images plays a significant role in ophthalmologic disease diagnosis. High performance pre-processing of the colour images was performed. International Journal of Electrical and Computer Engineering. Finally, experiment for NVD and NVE detection has been carried out with DIARET-DB1 data-set. All around the world, partial or total blindness has become a direct consequence of diabetes and hypertension. Tracing of vessels is done via forward detection, bifurcation identification, and backward verification. The novel vessel segmentation method starts with the contrast adjustment of the green channel image representation to increase the dynamic range of the gray levels, so that the vessels will appear brighter than the background. Front Aging Neurosci. Grosso A., Cheung N., Veglio F., Wong T. Y.

Arteriole-to-venule ratio (AVR), tortuosity index (TI), and mean fractal dimension (mean-D) carried out by.

Performance measurement using the parameters of accuracy, positive prediction value (PPV), negative prediction value (NPV), sensitivity, specificity and area under the curve (AUC). AVR and mean-D were lower than control in both patients with hypertensive retinopathy and CADASIL (P < 0.05). So the model could classify retinal image into one of two classes, namely the normal retina and retina with high blood pressure, based on the BNN output result. doi: 10.1212/01.wnl.0000179177.15900.ca.

Certainly. Severe case of hypertensive retinopathy causes systematic aliments that may cause cardiovascular diseases, heart and renal failure, loss of vision and finally death. This paper proposes an automated blood vessel detection scheme based on adaptive contrast enhancement, feature extraction, and tracing. The increment of TI was significant in HR and uncertain in CADASIL group. It can happen at any stage, but it’s more likely to happen as the condition advances. From an individual retinal photograph, vessel tracking and vessel segment selection is carried out by means of the, Box plots illustrating group differences in arteriole-to-venule ratio (AVR), mean fractal dimension (mean-D), and tortuosity index (TI) of the retinal vessels. The proposed algorithm being simple and easy to implement, is best suited for fast processing applications. National Eye Institute: “Facts About Diabetic Eye Disease.”, National Health Service: “Diabetic Retinopathy.”, American Academy of Ophthalmology: “What Is Diabetic Retinopathy?”. 2005;206(4):319–348. The contrast of the microaneurysms and hemorrhages, regarding the background, is improved substantially.