1. A method comprising: receiving, by a computing device, an image, wherein the image comprises a digital color fundus image comprising a border around a field of view; mirroring one or more pixel values in the image from within the border to outside the field of view; blurring the image with a filter and subtracting the blurred image from the image to remove slow background variations, resulting in a preprocessed image; identifying one or more vessel pixels in the preprocessed image as representing arteries and one or more other vessel pixels in the preprocessed image as representing veins in the field of view, by performing vessel segmentation on the preprocessed image and utilizing a trained classifier to disambiguate arterial vessel pixels from venous vessel pixels, wherein the trained classifier is trained based on a set of training images, resulting in a vessel likelihood map comprising a plurality of vessels; applying a tobogganing method to the preprocessed image, resulting in a splat map; determining, for each splat of the slap map, based on the vessel likelihood map, whether a splat is inside or outside a vessel, resulting in a processed vessel likelihood map; applying a skeletonization method to the processed vessel likelihood map to reduce each of the plurality of vessels to a single respective centerline comprised of centerline pixels; removing cross-over points and bifurcation points of the respective centerlines the processed vessel likelihood map to subdivide the processed vessel likelihood map into a plurality of vessel segments, each labeled as an artery vessel segment or a vein vessel segment; defining a region of interest in the processed vessel likelihood map centered on a centerpoint of an optic disc; removing vessels segments from the plurality of vessel segments that are outside the region of interest; determining, by the computing device, vessel width measurements for the plurality of vessel segments, wherein the vessel width measurement is measured by, for each centerline pixel, determining a left vessel edge and a right vessel edges in the processed vessel likelihood map and calculating the distance between the left vessel edge and the right vessel edge; and estimating, by the computing device, from the vessel width measurements an arteriovenous ratio (AVR).