This project proposes a glaucomatous image classification using texture features within images and it will be classified effectively based on feature ranking and neural network. In addition with, an efficient detection of exudates for retinal vasculature disorder analysis performed. The states of retinal blood vessels can be used to detect some diseases like diabetes. The important texture feat...

Image processing, analysis and computer vision techniques are found today in all fields of medical science. These techniques are especially relevant to modern ophthalmology, a field heavily dependent on visual data. Retinal images are widely used for diagnostic purposes by ophthalmologists. However, these images often need visual enhancement prior to apply a digital analysis for pathological ri...

Retinal Blood vessel morphology can be an important indicator for many diseases such as diabetes mellitus, hypertension and arteriosclerosis. The measurement of geometrical changes in retinal veins and arteries can be applied to a variety of clinical studies. The spotlight of this paper is developing the screening system with the aim of highly accurate and automated analysing tool for the ophth...

Diabetic Retinopathy is one of the leading causes of blindness. Hard exudates have been found to be one of the most prevalent earliest clinical signs of retinopathy. Thus, identification and classification of hard exudates from retinal images is clinically significant. For this purpose the images from the hospitals were taken as reference. In this work, Genetic Algorithm (GA) for best feature s...

In this paper, a system for automated analysis of retinal images is proposed. This system segments blood vessels in retinal images and recognizes the main features of the fundus on digital color images. The recognized features were defined as blood vessels, optic disc, and fovea. An algorithm called 2D matched filters response has been proposed for the detection of blood vessels. Also, automati...

The retinal fundus photograph is widely used in the diagnosis and treatment of various eye diseases such as diabetic retinopathy and glaucoma. Medical image analysis and processing has great significance in the field of medicine. Segmentation in eye imaging provides an important role for calculating the geometric shape and size of optic disc and anterior segment and abnormal growth of any regio...

The analysis of retinal images is becoming a vital medical tool to predict retinopathy and other retinal impairments. The algorithms implemented on CPU are able to process retinal images. However, the algorithms running on CPU are executed sequentially. This is due to the hardware limitation of CPU. GPU are having inherent hardware architecture to enable parallel implementation of image process...