Principal Warps: Thin-Plate Splines and the Decomposition of Deformations
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Object modelling by registration of multiple range images
Image and Vision Computing - Special issue: range image understanding
Iterative point matching for registration of free-form curves and surfaces
International Journal of Computer Vision
Active shape models—their training and application
Computer Vision and Image Understanding
Parametrization of closed surfaces for 3-D shape description
Computer Vision and Image Understanding
A morphable model for the synthesis of 3D faces
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
3D Statistical Shape Models Using Direct Optimisation of Description Length
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
MICCAI '98 Proceedings of the First International Conference on Medical Image Computing and Computer-Assisted Intervention
Small Sample Size Learning for Shape Analysis of Anatomical Structures
MICCAI '00 Proceedings of the Third International Conference on Medical Image Computing and Computer-Assisted Intervention
ISBMS '08 Proceedings of the 4th international symposium on Biomedical Simulation
MIAR '08 Proceedings of the 4th international workshop on Medical Imaging and Augmented Reality
ICDHM'07 Proceedings of the 1st international conference on Digital human modeling
IPCAI'10 Proceedings of the First international conference on Information processing in computer-assisted interventions
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Miar'06 Proceedings of the Third international conference on Medical Imaging and Augmented Reality
A novel 3d/2d correspondence building method for anatomy-based registration
WBIR'06 Proceedings of the Third international conference on Biomedical Image Registration
IPCAI'12 Proceedings of the Third international conference on Information Processing in Computer-Assisted Interventions
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Constructing anatomical shape from extremely sparse information is a challenging task. A priori information is often required to handle this otherwise ill-posed problem. In the present paper, we try to solve the problem in an accurate and robust way. At the heart of our approach lies the combination of a three-stage anatomical shape reconstruction technique and a dense surface point distribution model (DS-PDM). The DS-PDM is constructed from an already-aligned sparse training shape set using Loop subdivision. Its application facilitates the setup of point correspondences for all three stages of surface reconstruction due to its dense description. The proposed approach is especially useful for accurate and stable surface reconstruction from sparse information when only a small number of a priori training shapes are available. It adapts gradually to use more information derived from the a priori model when larger number of training data are available. The proposed approach has been successfully validated in a preliminary study on anatomical shape reconstruction of two femoral heads using only dozens of sparse points, yielding promising results.