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
Active shape models—their training and application
Computer Vision and Image Understanding
The 3D marching lines algorithm
Graphical Models and Image Processing
Generation of point-based 3D statistical shape models for anatomical objects
Computer Vision and Image Understanding - Special issue on analysis of volumetric image
Scattered Data Interpolation with Multilevel B-Splines
IEEE Transactions on Visualization and Computer Graphics
3D Statistical Shape Models Using Direct Optimisation of Description Length
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
A Unified Framework for Atlas Matching Using Active Appearance Models
IPMI '99 Proceedings of the 16th International Conference on Information Processing in Medical Imaging
MICCAI '01 Proceedings of the 4th International Conference on Medical Image Computing and Computer-Assisted Intervention
Groupwise rigid registration of wrist bones
MICCAI'12 Proceedings of the 15th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II
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The aims of this paper are to devise robust methods for the description of the variability in shapes of long bones using 3D statistical shape models (SSMs), and to test these on a dataset of humeri that demonstrate significant variability in shape. 30 primate humeri were CT scanned and manually segmented. SSMs were constructed from a training set of landmarks. The landmarks of the 3D shapes are extracted automatically using marching cubes and point correspondences are automatically obtained via a volumetric non-rigid registration technique using multiresolution B-Spline deformations. The surface registration resulted in no discernible differences between bone shapes, demonstrating the high accuracy of the registration method. An analysis of variations is applied on the shapes based on the model we built. The first mode of variation accounted for 42% of the variation in bone shape. This single component discriminated directly between great apes (including humans) and monkeys.