Tree matching applied to vascular system

In this paper, we propose an original tree matching algorithm for intra-patient hepatic vascular system registration. The vascular systems are segmented from CT-Scan images acquired at different time, and then modeled as trees. The goal of this algorithm is to find common bifurcations (nodes) and vessels (edges) in both trees. Starting from the tree root, edges and nodes are iteratively matched. The algorithm works on a set of matching hypotheses which is updated to keep best matches. It is robust against topological modification, as the segmentation process can fail to detect some branches. Finally, this algorithm is validated on the Visible Human with synthetic deformations thanks to the simulator prototype developed at the INRIA which provides realistic deformations for liver and its vascular network.