Parametrization of closed surfaces for 3-D shape description
Computer Vision and Image Understanding
Shape Analysis of Brain Ventricles Using SPHARM
MMBIA '01 Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA'01)
Automatic and Robust Computation of 3D Medial Models Incorporating Object Variability
International Journal of Computer Vision - Special Issue on Research at the University of North Carolina Medical Image Display Analysis Group (MIDAG)
Statistical variability in nonlinear spaces: application to shape analysis and dt-mri
Statistical variability in nonlinear spaces: application to shape analysis and dt-mri
Statistics of shape via principal geodesic analysis on lie groups
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
A General and Unifying Framework for Feature Construction, in Image-Based Pattern Classification
IPMI '09 Proceedings of the 21st International Conference on Information Processing in Medical Imaging
Statistics of pose and shape in multi-object complexes using principal geodesic analysis
Miar'06 Proceedings of the Third international conference on Medical Imaging and Augmented Reality
Tree-space statistics and approximations for large-scale analysis of anatomical trees
IPMI'13 Proceedings of the 23rd international conference on Information Processing in Medical Imaging
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We present a method for two-sample hypothesis testing for statistical shape analysis using nonlinear shape models. Our approach uses a true multivariate permutation test that is invariant to the scale of different model parameters and that explicitly accounts for the dependencies between variables. We apply our method to m-rep models of the lateral ventricles to examine the amount of shape variability in twins with different degrees of genetic similarity.