Active shape models—their training and application
Computer Vision and Image Understanding
Multi-scale EM-ICP: A Fast and Robust Approach for Surface Registration
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Laplace-Beltrami spectra as 'Shape-DNA' of surfaces and solids
Computer-Aided Design
Non-rigid surface registration using spherical thin-plate splines
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention - Volume Part I
International Journal of Computer Vision
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Problems of dense partial correspondence for meshes of variable topology are ubiquitous in medical imaging. In particular, this problem arises when constructing average shapes and probabilistic atlases of partial skull models. We exploit the roughly spherical extrinsic geometry of the skull to first approximate skull models with shapes of spherical topology. The skulls are then matched parametrically via a non-local non-linear landmark search using normalized spherical cross-correlation of curvature features. A dense spherical registration algorithm is then applied for a final correspondence. We show that the non-local step is crucial for accurate mappings. We apply the entire pipeline to low SNR skull meshes extracted from conical CT images. Our results show that the approach is robust for creating averages for families of shapes that deviate significantly from local isometry.