Monte Carlo Tree Search for 3D/2D Registration of Vessel Graphs

3D/2D registration techniques can compensate for the deficiencies of X-ray angiography-based navigation in vascular interventional surgery, such as the lack of depth information and excessive use of contrast agents. In this study, we propose a novel Monte Carlo tree search-based 3D/2D vessel graph registration method. The registration problem is transferred to a tree search problem according to the topology of vessel centerlines. Then, the Monte Carlo tree search method is applied to find the optimal vessel matching associated with highest registration score. Experiments on uninitialized vessel data demonstrate that the proposed method can achieve the highest accuracy among four state-of-the-art methods. An average accuracy of 1.91 mm on clinical coronary artery data is obtained. For the independence of initial pose and robustness to noise, the proposed method can align 3D and 2D vessels without prior initialization in vascular interventional surgery.