I’m working with eye fundus (retina) images. I segment the vessel tree as a binary image from the fundus image (currently experimenting with Weka). Then I skeletonize the vessel tree to obtain the centerline of the vessels. Then I need to map each point on the vessel tree to the closest skeleton point. I’ve been doing this in a somewhat inefficient, unelegant way by iterating over a square around each point to find the skeleton point that minimizes the distance, but would like to improve on this.
I’m thinking of perhaps using the gradient of the distance map on the vessel tree to walk directly to the closest skeleton point (which would be the ridge of the distance map) or something like that. Does anyone know of some ready made solution/algorithm that can be adapted to do this? I would like to obtain two integer arrays of equal length:
a=[index of vessel map points] and
b=[index of corresponding skeleton point] (with
index=x+y*width). Any ideas?
Thank for any tips!