We present a quantitative method for the comparison of vascular topology and geometry measured from retinal fundus photographs. The measure compares the difference between distributions taken from a graph representation of the vasculature, which is derived by image segmentation. The measure uses the Kullback-Leibler distance between statistical measures on the reference and test segmentations which can be geometrical, like the distribution of vessel widths, or topological, like local connectivity or a combination of the two.
The user is free to build any meaningful description and here we illustrate two local topology measures graphically. Using this assessment method, we also show that our model based segmentation method has better geometrical accuracy than a technique based on matched filtering. We have tested out the measures on a set of 20 images from the STARE project data.