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
Active shape models—their training and application
Computer Vision and Image Understanding
A Statistical Shape Model for the Liver
MICCAI '02 Proceedings of the 5th International Conference on Medical Image Computing and Computer-Assisted Intervention-Part II
Construction of 3D Shape Models of Femoral Articular Cartilage Using Harmonic Maps
MICCAI '00 Proceedings of the Third International Conference on Medical Image Computing and Computer-Assisted Intervention
Greedy optimal homotopy and homology generators
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
Meshing genus-1 point clouds using discrete one-forms
Computers and Graphics
Statistical Models of Shape: Optimisation and Evaluation
Statistical Models of Shape: Optimisation and Evaluation
Mesh parameterization: theory and practice
ACM SIGGRAPH ASIA 2008 courses
Shape modeling and analysis with entropy-based particle systems
IPMI'07 Proceedings of the 20th international conference on Information processing in medical imaging
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For segmenting complex structures like vertebrae, a priori knowledge by means of statistical shape models (SSMs) is often incorporated. One of the main challenges using SSMs is the solution of the correspondence problem. In this work we present a generic automated approach for solving the correspondence problem for vertebrae. We determine two closed loops on a reference shape and propagate them consistently to the remaining shapes of the training set. Then every shape is cut along these loops and parameterized to a rectangle. There, we optimize a novel combined energy to establish the correspondences and to reduce the unavoidable area and angle distortion. Finally, we present an adaptive resampling method to achieve a good shape representation. A qualitative and quantitative evaluation shows that using our method we can generate SSMs of higher quality than the ICP approach.