摘要The introduction of path planning and visual navigation in vascular interventional surgery can provide an intuitive reference and guidance for doctors.In this study,based on the preprocessing results of vessel skeleton extraction and stenosis diagnosis in X-ray coronary angiography images,clustering is used to determine the connectivity of the intersection points,and then the improved Dijkstra algorithm is used to automatically plan the surgical path.On this basis,the intermediate point is introduced to piecewise correct the path and improve the accuracy of the system.Finally,the epipolar constrained inverse projection transformation is used to reconstruct the coronary artery 3D model,and the optimal path is marked to achieve a multi-angle 3D visual navigation.Clinical experimental results show that compared with the traditional Dijkstra algorithm,the improved method can reduce the need for intermediate points,which improves computational efficiency,and the average error of manual calibration path is reduced to 4％of that before overall optimization.The results of 3D reconstruction and reprojection further qualitatively and quantitatively verify the effectiveness of the whole scheme.