FEATURES EXTRACTION OF EYES USING ARTIFICIAL NEURAL NETWORK(ANN)

Ms. Kanchan S. Argade; Prof. Balbhim N. Bansode

Volume : VIII, Issue : V, May - 2019

FEATURES EXTRACTION OF EYES USING ARTIFICIAL NEURAL NETWORK(ANN)

Ms. Kanchan S. Argade, Prof. Balbhim N. Bansode

Abstract :

Diabetic retinopathy is the most common diabetic eye disease and a leading cause of blindness in the world. Diagnosis of diabetic retinopathy at an early stage can be done through the segmentation of blood vessels of the retina. In this work, the performance of descriptive statistical features in retinal vessel cellular division is evaluated by using an artificial neural network classifier (ANN). Early diagnosis is crucial in Diabetic Retinopathy (DR), to avoid further complications. The disease can be classified into one of two stages (an early stage of no proliferative and a later stage of proliferative diabetic retinopathy), diagnosed based on existence and quantity of a characteristic set of lesion in Eye Fundus Images (EFI). It is therefore important to segment sufficient regions of potential lesions, to highlight and classify the lesions and the degree of DR. Density clustering methods are favorable candidates to isolate individual lesions, and should be used together with effective techniques for vascular tree removal, feature extraction and classification. The experimental results confirmed that the descriptive statistical features can be employed in retinal vessel segmentation and can be used in rule–based and supervised classifiers