Intra-patient Non-rigid Registration of 3D Vascular Cerebral Images
Accuracy of intensity-based non-rigid registration of vascular images is deteriorated in the presence of excessive noise as occurring in CBCT angiography. A new approach to non-rigid registration of vascular images is presented based on the assumption of isometric deformation of vessel structures. For every voxel in the vascular image, the distances along the vessels to some reference voxels are computed as features that are invariant under isometric deformation. Due to the global information on vessel connectivity that is encoded in these features, voxel-based registration of these feature images can compensate for local optima in direct intensity-based registration of the vascular images. The method is validated in the context of brain-shift mitigation, but the technique can be used more broadly. Tests on artificially deformed vascular images show that our algorithm reaches higher accuracy than traditional intensity-based registration.
KeywordsWeighted Distance Vascular Image Brain Shift Minimal Cost Path Gaussian Pyramid
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