基于球形标记的多模态医学体配准

本文提出在医学多模态数据集 (尤其是 MRI和 CT)中基于球形人造标记的体配准过程。此过程或是半自动或是全自动完成的。半自动方法要求数据集中标出球形标记的近似点位置 ,再自动进行配准。全自动方法不需要用户的任何交互操作 ,即所有配准子任务 (球体的分割、寻找两组球体的对应关系、最后把第一套球体映射成第二套球体的几何变换的计算 )能由计算机自动执行。在全自动配准中 ,积聚器算法和迭代最近点算法的结合证明是一种有效的和鲁棒性好的点匹配方法

Multimodal medical volume registration based on spherical makers

Volume registraton procedures based on spherical artificial markers presented in medical multimodal data sets (especially MRI and CT) have been proposed.The procedures given are either semi automatic or fully automatic.A semi automatic approach requires to label approximate locations of the spherical markers in the data sets and then registration operates autonomically.All registration subtasks-namely segmentation of spheres,finding the correspondence between two sets of spheres and ,finally,computing geometrical transformation that maps the first set of spheres onto the second one-are performed automatically by the computer without any user interaction required by a fully automatic approach.In the case of the fully automatic approach,the combination of ICP algorithm and accumulator algorithm has proved to be a robust and efficient point matching strategy.