  We have developed and trained a convolutional neural network to automatically
and simultaneously segment optic disc, fovea and blood vessels. Fundus images
were normalised before segmentation was performed to enforce consistency in
background lighting and contrast. For every effective point in the fundus
image, our algorithm extracted three channels of input from the neighbourhood
of the point and forward the response across the 7 layer network. In average,
our segmentation achieved an accuracy of 92.68 percent on the testing set from
Drive database.
