A Coarse-to-Fine Surface Registration Algorithm for Frameless Brain Surgery

In this paper, we present a coarse-to-fine approach for surface registration used in frameless brain surgery. The reference point data are extracted from patient´s pre-stored CT images; the floating point data are captured from the patient´s head by using an electromagnetic tracker. The registration algorithm takes the information of global coarse markers (or feature points) and local fine point cloud into account to avoid the local optimum problem of the iterative closest point (ICP) algorithm. Experimental results show that the registration accuracy of using the proposed registration algorithm is improved than of using other ICP-related algorithms. More specifically, it shows that the target registration error (TRE) is decreased by 50% by using the proposed method.