Path descriptors for geometric graph matching and registration

Abstract

Graph and tree-like structures such as blood vessels and neuronal networks are abundant in medical imaging. We present a method to calculate path descriptors in geometrical graphs, so that the similarity between paths in the graphs can be determined efficiently. We show experimentally that our descriptors are more discriminative than existing alternatives. We further describe how to match two geometric graphs using our path descriptors. Our main application is registering images for which standard techniques are inefficient, because the appearance of the images is too different, or there is not enough texture and no uniquely identifiable keypoints to be found. We show that our approach can register these images with better accuracy than previous methods.