Characterization of two-year progression of neurodegeneration in different risk phenotypes of diabetic retinopathy

To characterize the two-year progression of neurodegeneration in different diabetic retinopathy (DR) risk phenotypes in type 2 diabetes.info:eu-repo/semantics/publishedVersio

Diagnostic circulating biomarkers to detect vision-threatening diabetic retinopathy: Potential screening tool of the future?

With the increasing prevalence of diabetes in developing and developed countries, the socio-economic burden of diabetic retinopathy (DR), the leading complication of diabetes, is growing. Diabetic retinopathy (DR) is currently one of the leading causes of blindness in working-age adults worldwide. Robust methodologies exist to detect and monitor DR; however, these rely on specialist imaging techniques and qualified practitioners. This makes detecting and monitoring DR expensive and time-consuming, which is particularly problematic in developing countries where many patients will be remote and have little contact with specialist medical centres. Diabetic retinopathy (DR) is largely asymptomatic until late in the pathology. Therefore, early identification and stratification of vision-threatening DR (VTDR) is highly desirable and will ameliorate the global impact of this disease. A simple, reliable and more cost-effective test would greatly assist in decreasing the burden of DR around the world. Here, we evaluate and review data on circulating protein biomarkers, which have been verified in the context of DR. We also discuss the challenges and developments necessary to translate these promising data into clinically useful assays, to detect VTDR, and their potential integration into simple point-of-care testing devices

Segementasi Optic Disk pada Penderita Diabetic Retinopathy Menggunakan GVF Snake

Efek dari diabetes pada mata disebut diabetic retinopathy (DR), berupa kerusakan pembuluh darah mikro (mikrovascular) pada mata. Pada tahap lanjut DR dapat mengakibatkan kebutaan. Segmentasi optic disk (OD) merupakan salah satu langkah penting dalam sistem diagnosa DR secara otomatis. Keberhasilan segmentasi OD ini sangat diperlukan untuk analisa lebih lanjut. Salah satunya untuk mendeteksi exudate: bercak pada mata yang merupakan akibat dari DR. Penelitian ini bertujuan untuk mendeteksi OD pada citra retina secara otomatis. Pendeteksian OD diawali dengan pre-processing untuk meningkatkan kualitas citra dan menghilangkan pembuluh darah. Selanjutnya kontur OD didapatkan dengan menggunakan GVF Snake. Hasil segmenatsi ini dibandingkan dengan hasil pendeteksian manual oleh dokter mata. Metode segmenatsi yang diusulkan berhasil mendeteksi OD dengan akurasi, sensitivitas dan spesifisitas masing-masing sebesar 99,81%, 97,12% dan 99,86%. Kata kunci: Diabetic retinopathy (DR), optic disk (OD), segmentasi, GVF snake

Why does diabetic retinopathy happen, and how can we stop it?

Diabetic retinopathy (DR) is a complication of diabetes. We can prevent DR both by preventing diabetes (primary prevention) and by improving the management of diabetes to slow down the onset, and reduce the severity, of DR (secondary prevention)

A Review on Vessel Extraction of Fundus Image to Detect Diabetic Retinopathy

Ophthalmology is an important term of medical field, which helps to visualize various diseases and treat them accordingly. Fundus images are processed so as to treat diseases like glaucoma, vein occlusions, and diabetic retinopathy (DR), obesity, glaucoma etc. There are types of supervised and unsupervised types of algorithms used so as to segment the Fundus images. There are three types of datasets available DRIVE, STARE and CHASE_DB1. These data sets are being segmented with the help of Laplace operator. This method makes preprocessing of images by using adaptive histogram equalization by CLAHE algorithm. The first step is to extract green channel and segment this image by using Laplace operator. Thus it helps to enhance extraction of blood vessels from fundus image. The detected blood vessels and measurement of these vessel is used for diagnosis of Diabetic Retinopathy (DR) and other eye diseases

The effect of combined renal and pancreatic transplantation on diabetic retinopathy

This case report describes the effect of simultaneous pancreas kidney transplant (SPK) on the diabetic retinopathy (DR) of two male type 1 diabetic patients. The literature on the effect of SPK on DR is reviewed and the evidence surrounding visual function outcomes is discussed

Fenofibrate reduces the severity of neuroretinopathy in a type 2 model of diabetes without inducing peroxisome proliferator-activated receptor alpha-dependent retinal gene expression

Fenofibrate slows the progression of clinical diabetic retinopathy (DR), but its mechanism of action in the retina remains unclear. Fenofibrate is a known agonist of peroxisome proliferator-activated receptor alpha (PPARα), a transcription factor critical for regulating metabolism, inflammation and oxidative stress. Using a DR mouse model

Artificial Intelligence and Deep Learning-Based System Design for Diabetic Retinopathy Classification

One of the biggest causes of avoidable blindness throughout the world is diabetic retinopathy (DR). There is a significant unmet need to test all diabetes patients for DR, and many instances of DR go undetected and untreated. In order to automate DR screening, this research aimed to create reliable diagnostic technologies. In order to reduce the pace of vision loss, it is important to refer eyes suspected of having DR to an ophthalmologist for further assessment and treatment. The primary goal of this research is to improve the classification accuracy for Diabetic Retinopathy (DR). In this script, we present a new neural network model for DR forecasting. The suggested model's accuracy in identifying DR phases was measured against that of regular and ensemble-based models. Various benchmark datasets, including MESSIDOR, IDRID, and APTOS, are used in the studies. The suggested DRPNN algorithm outperformed the competition in experiments assessed using industry-standard criteria

Automated detection of diabetic retinopathy in digiatal fundus images

Abstract : Diabetic Retinopathy (DR) is one of the leading causes of blindness in the industrialize