3D shape context is a method to define matching points between similar shapes as a pre-processing step to non-rigid registration. The main limitation of the approach is point mismatching, which includes long geodesic distance mismatch and neighbors crossing mismatch. In this paper, we propose a topological structure verification method to correct the long geodesic distance mismatch and a correspondence field smoothing method to correct the neighbors crossing mismatch. A robust 3D shape context model is proposed and further combined with thin-plate spline model for non-rigid surface registration. The method was tested on phantoms and rat hind limb skeletons from micro CT images. The results from experiments on mouse hind limb skeletons indicate that the approach is robust.
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