C. Ambroise, M. Dang, and G. Govaert, Clustering of Spatial Data by the EM Algorithm, Quantitative Geology and Geostatistics, vol.9, pp.493-504, 1997.
DOI : 10.1007/978-94-017-1675-8_40

G. Behiels, F. Maes, D. Vandermeulen, and P. Suetens, Evaluation of image features and search strategies for segmentation of bone structures in radiographs using Active Shape Models, Medical Image Analysis, vol.6, issue.1, pp.47-62, 2002.
DOI : 10.1016/S1361-8415(01)00051-2

F. Chung and H. Delingette, Multimodal Prior Appearance Models Based on Regional Clustering of Intensity Profiles, MICCAI 2009 -Proceedings of the 12th International Conference on Medical Image Computing and Computer Assisted Intervention, pp.1051-1058, 2009.
DOI : 10.1007/978-3-642-04271-3_127

URL : https://hal.archives-ouvertes.fr/inria-00616132

T. Cootes and C. Taylor, Data Driven Refinement of Active Shape Model Search, Procedings of the British Machine Vision Conference 1996, 1996.
DOI : 10.5244/C.10.10

T. Cootes and C. Taylor, Statistical models of appearance for computer vision, 2004.

T. Cootes, A. Hill, C. Taylor, and J. Haslam, The use of active shape models for locating structures in medical images, IPMI'93 -Proceedings of the 13th International Conference on Information Processing in Medical Imaging, pp.33-47, 1993.

T. Cootes, G. Edwards, and C. Taylor, Active appearance models, IEEE Pattern Analysis and Machine Intelligence, vol.23, issue.6, p.681685, 2001.

H. Delingette, General object reconstruction based on simplex meshes, International Journal of Computer Vision, vol.32, issue.2, pp.111-146, 1999.
DOI : 10.1023/A:1008157432188

URL : https://hal.archives-ouvertes.fr/inria-00073579

B. Gilles and N. Magnenat-thalmann, Musculoskeletal MRI segmentation using multi-resolution simplex meshes with medial representations, Medical Image Analysis, vol.14, issue.3, pp.291-302, 2010.
DOI : 10.1016/j.media.2010.01.006

C. Goodall, Procrustes methods in the statistical analysis of shape, Journal of the Royal Statistical Society Series BMethodological), vol.53, issue.2, pp.285-339, 1991.

J. Gower, Generalized procrustes analysis, Psychometrika, vol.35, issue.1, pp.33-51, 1975.
DOI : 10.1007/BF02291478

T. Heimann and H. Meinzer, Statistical shape models for 3D medical image segmentation: A review, Medical Image Analysis, vol.13, issue.4, pp.543-563, 2009.
DOI : 10.1016/j.media.2009.05.004

T. Heimann, S. Munzing, H. Meinzer, and I. Wolf, A Shape-Guided Deformable Model with Evolutionary Algorithm Initialization for 3D Soft Tissue Segmentation, IPMI 2007 -Proceedings of the 20th International Conference on Information Processing in Medical Imaging, pp.1-12, 2007.
DOI : 10.1007/978-3-540-73273-0_1

M. Holden, D. Hill, E. Denton, J. Jarosz, T. Cox et al., Voxel Similarity Measures for 3D Serial MR Brain Image Registration, IPMI'99 -Proceedings of the 16th International Conference on Information Processing in Medical Imaging, pp.472-477, 1999.
DOI : 10.1007/3-540-48714-X_48

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.80.3387

I. Jolliffe, Principal Component Analysis, 2002.
DOI : 10.1007/978-1-4757-1904-8

D. Kim, K. Lee, and D. Lee, On cluster validity index for estimation of the optimal number of fuzzy clusters, Pattern Recognition, vol.37, issue.10, pp.2009-2025, 2004.
DOI : 10.1016/j.patcog.2004.04.007

J. Schäfer and K. Strimmer, A Shrinkage Approach to Large-Scale Covariance Matrix Estimation and Implications for Functional Genomics, Statistical Applications in Genetics and Molecular Biology, vol.4, issue.1, 2005.
DOI : 10.2202/1544-6115.1175

J. Schmid and N. Magnenat-thalmann, MRI Bone Segmentation Using Deformable Models and Shape Priors, MICCAI 2008 -Proceedings of the 11th International Conference on Medical Image Computing and Computer Assisted Intervention, pp.119-126, 2008.
DOI : 10.1007/978-3-540-85988-8_15

J. Schmid, A. Sandholm, F. Chung, D. Thalmann, H. Delingette et al., Musculoskeletal simulation model generation from MRI datasets and motion capture data, pp.3-19, 2009.
URL : https://hal.archives-ouvertes.fr/inria-00616096

J. Schmid, J. Kim, and N. Magnenat-thalmann, Extreme leg motion analysis of professional ballet dancers via MRI segmentation of multiple leg postures, Press available online, 2010.
DOI : 10.1007/s11548-010-0474-z

H. Seim, D. Kainmueller, M. Heller, H. Lamecker, S. Zachow et al., Automatic segmentation of the pelvic bones from ct data based on a statistical shape model, Eurographics Workshop on Visual Computing for Biomedicine, Eurographics Association, pp.93-100, 2008.

M. Styner, C. Brechbühler, G. Székely, and G. Gerig, Parametric estimate of intensity inhomogeneities applied to MRI, IEEE Transactions on Medical Imaging, vol.19, issue.3, pp.153-165, 2000.
DOI : 10.1109/42.845174

S. Tadjudin and D. Landgrebe, Covariance estimation with limited training samples, IEEE Transactions on Geoscience and Remote Sensing, vol.37, issue.4, pp.2113-2118, 1999.
DOI : 10.1109/36.774728