Detection of Retinopathy Diseases Using an Artificial Neural Network Based On the Discrete Cosine Transform

Summary


The retinopathy diseases occur when the neurons do not transmit signals from retina to the brain. These disorders are: Diabetic retinopathy, hypertensive retinopathy, macular degeneration, vein branch occlusion, vitreous hemorrhage, and normal retina. This work presents a novel detection algorithm about retinopathy disorders from retina images. For this purpose, the retina images were pre-processed and resized at first. Then the discrete cosine transform was used as feature extraction before applying a neural network classifier. The performance of recognition rates of the novel detection algorithm were found as 50%, 70%, 85%, 90%, and 95% for testing five retinopathy cases respectively.

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Detection of Retinopathy Diseases Using an Artificial Neural Network Based On the Discrete Cosine Transform

1. Introduction

The retina is light-sensitive tissue at the back of the eye. A healthy retina is necessary for good vision. Electrophysiological tests reveal an abnormal function of the visual system in patients with diabetic retinopathy. It is a common cause of visual loss in the world, and it is a potentially blinding complication of diabetes that damages the eye retina. The growth of new blood v...

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