Acquisition of point cloud in CT image space to improve accuracy of surface registration: Application to neurosurgical navigation system

Abstract

One important technique of surgical navigation is surface registration that matches coordinates in two different spaces. We proposed a novel method to extract an optimal point cloud in image space corresponding to the point cloud in patient space to improve the registration accuracy. In the hemispherical study, our proposed method demonstrated a reduced surface registration error (SRE) and target registration error (TRE) compared to the conventional method in all cases (number of points, distribution, noise). In the phantom study, the SRE and TRE were low and stable in the proposed method, with SRE reduced by 22 % and TRE by 18 % (p < 0.05). The proposed method was not affected by the number of points, distribution, or noise in the point cloud, and it could improve the registration accuracy without the aid of additional equipment.