Charnoz Arnaud, Agnus Vincent, Malandain Grégoire, Nicolau Stéphane, Tajine Mohamed, Soler Luc
IRCAD R&D, Strasbourg, France.
Inf Process Med Imaging. 2005;19:443-55. doi: 10.1007/11505730_37.
In this paper, we propose an original and efficient tree matching algorithm for intra-patient hepatic vascular system registration. Vascular systems are segmented from CT-scan images acquired at different times, 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 match solutions that are updated to keep the best matches thanks to a quality criterion. It is robust against topological modifications due to segmentation failures and against strong deformations. Finally, this algorithm is validated on a large synthetic database containing cases with various deformation and segmentation problems.
在本文中，我们提出了一种用于患者体内肝血管系统配准的原创且高效的树形匹配算法。从在不同时间获取的CT扫描图像中分割出血管系统，然后将其建模为树。该算法的目标是在两棵树中找到共同的分叉点（节点）和血管（边）。从树根开始，边和节点被迭代匹配。该算法基于一组匹配解决方案进行工作，这些解决方案会根据质量标准进行更新，以保留最佳匹配。它对于因分割失败导致的拓扑修改以及强烈变形具有鲁棒性。最后，该算法在一个包含各种变形和分割问题案例的大型合成数据库上得到了验证。
