In this paper, we have tested and validated a vessel-based registration technique for correction of brain-shift using retrospective clinical data from five patients: three patients with brain tumors, one patient with an aneurysm and one patient with an arteriovenous malformation. The algorithm uses vessel centerlines extracted from segmented pre-operative MRA data and intra-operative power Doppler ultrasound images to compute first a linear fit and then a thin-plate spline transform in order to achieve non-linear registration. The method was validated using (i) homologous landmarks identified in the original data, (ii) selected vessels, excluded from the fitting procedure and (iii) manually segmented, non-vascular structures. The tracking of homologous landmarks show that we are able to correct the deformation to within 1.25 mm, and the validation using excluded vessels and anatomical structures show an accuracy of 1mm. Pre-processing of the data can be completed in 30 s per dataset, and registrations can be performed in less than 30s. This makes the technique well suited for intra-operative use.