Automated early detection of multiple diseases from retinal Fundus images: A Review

Abstract

Now a days there are large number of disease such as cardiovascular, diabetic retinopathy and lung diseases which will damage the optic nerve head that results in the loss of vision. Manually it is not possible to find the disease at earlier stages The diagnoses require regular monitoring of retinal fundus images that consumes more time and costlier. The accuracy and reliability of the diagnosis depends upon the ophthalmologist’s domain knowledge. Therefore the requirement for automatic diagnosis of multiple eye diseases is needed. This paper surveys automatic extraction of multiple diseases from the retinal fundus images. This paper evaluates the existing automated early detection of multiple eye disease extraction methods based on Convolution neural network, multi-sieving Convolutional neural network and back propagation network.