Abnormality detection plays an important role in many real-life applications. Retinal vessel segmentation algorithms are the critical components of circulatory blood vessel Analysis systems for detecting the various abnormalities in retinal images. Traditionally, the vascular network is mapped by hand in a time-consuming process that requires both training and skill. Automating the process allo...

The field of medical imaging gains its importance with increase in the need of accurate and efficient diagnosis over a short period of time. Since manual processes are tedious, time consuming and impractical for large data there is a need for automatic processing that helps community health workers. Retinal blood vessel segmentation in diabetic retinopathy plays an important role in diagnosing ...

This paper investigates the image processing techniques to identify blood vessels in the retinal images. Each identified vessel is stored and labelled with a number which also indicating whether the vessel originates from the optic disc or it is a branch of a vessel which originates from the optic disc. Non-linear fitting technique is used to process each point on blood vessels locally. The alg...

Detecting blood vessels is a vital task in retinal image analysis. The task is more challenging with the presence of bright and dark lesions in retinal images. Here, a method is proposed to detect vessels in both normal and abnormal retinal fundus images based on their linear features. First, the negative impact of bright lesions is reduced by using K-means segmentation in a perceptive space. T...

A new method to extract retinal blood vessels from a colour fundus image is described. Digital colour h d u s images are contrast enhanced in order to obtain sharp edges. The green bands are selected and transformed to correlation coefficient images by using two sets of Gaussian kernel patches of distinct scales of resolution. Blood vessels are then extracted by means of a new algorithm, direct...

Automated extraction of retinal vessels play an important role in the diagnosis of a wide range of retinal diseases and also for diagnosing complications due to cardiovascular diseases, stroke and hypertension. The blood vessels of the retina are a complex network and manual segmentation of them is a prolong and tedious task which requires high skills and training. In this paper, a novel method...

PURPOSE To report a case of Coats' disease in which spontaneous reattachment occurred after total retinal detachment. PATIENT AND METHODS A young boy (patient age: 4 years and 11 months) presented with leukocoria in the left eye. Slit-lamp examination revealed total retinal detachment with abnormal retinal blood vessels and subretinal exudation just behind the lens. Computed tomography imagin...

The correct segmentation of blood vessels in optical coherence tomography (OCT) images may be an important requirement for the analysis of intra-retinal layer thickness in human retinal diseases. We developed a shape model based procedure for the automatic segmentation of retinal blood vessels in spectral domain (SD)-OCT scans acquired with the Spectralis OCT system. The segmentation procedure ...

The retina has a high rate of oxygen consumption, and the retinal vessels are knoion to constrict with increased arterial oxygen tension and dilate ivhen arterial oxygen falls. In 10 subjects, measurement of retinal venous oxygen saturation by a photographic technique has shown an increase from 55 ± 8 per cent saturation breathing air to 82 ± 9 per cent breathing 100 per cent Os. This increase ...