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Trajectory planning for vascular navigation from 3D angiography images and vessel centerline data

机译:3D血管造影图像和船舶中心线数据的血管导航轨迹规划

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A recently introduced method for robotic vascular catheterization is Fringe Field Navigation (FFN). A requirement of this method is the trajectory required for planning the sequences of navigation. We have introduced a method of trajectory planning compatible with the requirements of FFN for vasculature navigation. The method exploits the vessel centerline to define the vascular structure trajectory as a tree network by finding the vertices connecting the labelled nodes based on distance and direction criteria possible vertices. It follows a progressive algorithm to find the required distance thresholds for defining vertices that build up a tree network model and consequently a trajectory for navigation need. The method has been implemented on different examples of cerebrovascular arteries and a three-dimensional model of the portal artery of a porcine. The method successfully produced the trajectory and location of bifurcation and vertices.
机译:最近引入的机器人血管导管术方法是边缘场导航(FFN)。这种方法的要求是规划导航序列所需的轨迹。我们介绍了一种兼容FFN用于血管系统导航的要求的轨迹规划方法。该方法利用血管中心线以通过查找基于距离和方向标准的顶点来确定连接标记节点的顶点作为树网络定义血管结构轨迹。它遵循逐行算法找到用于定义构建树网络模型的顶点的所需距离阈值,从而进行导航需要的轨迹。该方法已经在脑血管动脉的不同实例中实施,猪的门静脉动脉的三维模型。该方法成功地产生了分叉和顶点的轨迹和位置。

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