Matching Hierarchical Structures Using Association Graphs
IEEE Transactions on Pattern Analysis and Machine Intelligence
MICCAI '02 Proceedings of the 5th International Conference on Medical Image Computing and Computer-Assisted Intervention-Part II
Tracking 3-D Pulmonary Tree Structures
MMBIA '96 Proceedings of the 1996 Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA '96)
Registration and Analysis of Vascular Images
International Journal of Computer Vision - Special Issue on Research at the University of North Carolina Medical Image Display Analysis Group (MIDAG)
Liver registration for the follow-up of hepatic tumors
MICCAI'05 Proceedings of the 8th international conference on Medical image computing and computer-assisted intervention - Volume Part II
Matching of anatomical tree structures for registration of medical images
Image and Vision Computing
Matching of tree structures for registration of medical images
GbRPR'07 Proceedings of the 6th IAPR-TC-15 international conference on Graph-based representations in pattern recognition
Hierarchical matching of anatomical trees for medical image registration
ICMB'08 Proceedings of the 1st international conference on Medical biometrics
Geometries on spaces of treelike shapes
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part II
Efficient globally optimal matching of anatomical trees of the liver
EG VCBM'10 Proceedings of the 2nd Eurographics conference on Visual Computing for Biology and Medicine
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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.