S. Allassonnière, E. Kuhn, and A. Trouvé, MAP estimation of statistical deformable templates via nonlinear mixed eects models : Deterministic and stochastic approaches, Proc. of the International Workshop on the Mathematical Foundations of Computational Anatomy (MFCA- 2008), 2008.

G. Auzias, Recalage interindividuel de surfaces corticales par déformations diéomorphiques, 2009.

G. Auzias, J. Glaunes, O. Colliot, M. Perrot, J. Mangin et al., DISCO : A coherent dieomorphic framework for brain registration under exhaustive sulcal constraints. Medical Image Computing and Computer-Assisted InterventionMICCAI, p.730738, 2009.
DOI : 10.1007/978-3-642-04268-3_90

D. J. Blezek and J. V. Miller, Atlas stratication, Medical Image Analysis, vol.11, issue.5, p.443457, 2007.

F. L. Bookstein, Principal warps: thin-plate splines and the decomposition of deformations, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.11, issue.6, p.567585, 1989.
DOI : 10.1109/34.24792

E. Ceyhan, M. Beg, C. Ceritoglu, L. Wang, J. Morris et al., Quantization and analysis of hippocampal morphometric changes due to dementia of Alzheimer type using metric distances based on large deformation dieomorphic metric mapping . Computerized Medical Imaging and Graphics, The Ocial Journal of the Computerized Medical Imaging Society, vol.35, issue.4, p.275293, 2011.

Y. Cheng, Mean shift, mode seeking, and clustering, IEEE Trans. Pattern Anal. Mach. Intell, vol.17, issue.8, p.790799, 1995.

M. Chupin, . Lehéricy, . Hasboun, . Colliot, . Goerke et al., Segmenting the subregions of the human hippocampus at 7 Tesla, S122, 2009. Organization for Human Brain Mapping Annual Meeting, p.47
DOI : 10.1016/S1053-8119(09)71156-5

D. L. Collins, Model-based segmentation of individual brain structures from magnetic resonance imaging data, 1994.

G. Davis, S. Mallat, and M. Avellaneda, Adaptive greedy approximations, Constructive Approximation, vol.21, issue.1, p.5798, 1997.
DOI : 10.1007/BFb0112501

URL : ftp://cs.nyu.edu/pub/wave/report/AdaptApprox.ps.Z

S. Durrleman, X. Pennec, A. Trouvé, and N. Ayache, Statistical models of sets of curves and surfaces based on currents, Medical Image Analysis, vol.13, issue.5, p.793808, 2009.
DOI : 10.1016/j.media.2009.07.007

URL : https://hal.archives-ouvertes.fr/hal-00816051

H. Duvernoy, The Human Hippocampus : An Atlas of Applied Anatomy, 1988.

J. Glaunes, Transport par diéomorphismes de points, de mesures et de courants pour la comparaison de formes et l'anatomie numérique, 2005.

J. Glaunès and S. Joshi, Template estimation from unlabeled point set data and surfaces for computational anatomy, Proc. of the International Workshop on the Mathematical Foundations of Computational Anatomy (MFCA-2006), p.2939, 2006.

J. Glaunes, A. Qiu, M. I. Miller, and L. Younes, Large deformation dieomorphic metric curve mapping, International Journal of Computer Vision, vol.80, issue.3, p.317336, 2008.

J. Glaunes, A. Trouvé, and L. Younes, Dieomorphic matching of distributions : A new approach for unlabelled point-sets and sub-manifolds matching, Computer Vision and Pattern Recognition, p.712718, 2004.

S. Joshi and M. Miller, Landmark matching via large deformation dieomorphisms, IEEE Transactions on Signal Processing, vol.9, issue.8, p.13571370, 2000.
DOI : 10.1109/83.855431

R. Kothari and D. Pitts, On nding the number of clusters, Pattern Recognition Letters, vol.20, issue.4, p.405416, 1999.

P. Lorenzen, B. Davis, and S. C. Joshi, Unbiased atlas formation via large deformations metric mapping. Medical Image Computing and Computer-Assisted InterventionMICCAI, p.411418, 2005.
DOI : 10.1007/11566489_51

J. F. Lu, J. B. Tang, Z. M. Tang, and J. Y. Yang, Hierarchical initialization approach for K-Means clustering, Pattern Recognition Letters, vol.29, issue.6, p.787795, 2008.
DOI : 10.1016/j.patrec.2007.12.009

L. Van-der-maaten, E. Postma, J. Van-den, and . Herik, Dimensionality reduction : A comparative review, p.35, 2009.

S. Mallat and Z. Zhang, Matching pursuits with time-frequency dictionaries, IEEE Transactions on Signal Processing, vol.41, issue.12, p.33973415, 1993.
DOI : 10.1109/78.258082

URL : http://home.ustc.edu.cn/~zhanghan/cs/Mallat_Zhang93.pdf

J. Mazziotta, A. Toga, A. Evans, P. Fox, and J. Lancaster, A probabilistic atlas of the human brain : theory and rationale for its development : International consortium for brain mapping (ICBM), NeuroImage, issue.22PA, p.89101, 1995.

J. Mazziotta, A. Toga, A. Evans, P. Fox, J. Lancaster et al., A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM), Philosophical Transactions of the Royal Society B: Biological Sciences, vol.356, issue.1412, p.356, 1412.
DOI : 10.1098/rstb.2001.0915

A. Ng, M. Jordan, and Y. Weiss, On spectral clustering : Analysis and an algorithm, ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 14 : Proceeding of the 2001 Conference, p.849856, 2001.

D. Pelleg and A. W. Moore, X-means : Extending k-means with ecient estimation of the number of clusters, The International Conference on Machine Learning (ICML), pp.727-734, 2000.

Z. , Y. Sun, M. Perrot, A. Tucholka, D. Rivière et al., Constructing a dictionary of human brain folding patterns, MICCAI, p.117124, 2009.
URL : https://hal.archives-ouvertes.fr/hal-00776671

Z. Y. Sun, Inférence d'un dictionnaire des motifs des plissements corticaux, 2011.

J. Talairach and P. Tournoux, Co-planar stereotactic atlas of the human brain : 3-dimensional proportional system : an approach to cerebral imaging, p.122, 1988.

J. Tenenbaum, V. Silva, and J. Langford, A Global Geometric Framework for Nonlinear Dimensionality Reduction, Science, vol.290, issue.5500, p.23192323, 2000.
DOI : 10.1126/science.290.5500.2319

L. Wang, F. Beg, T. Ratnanather, C. Ceritoglu, L. Younes et al., Large deformation dieomorphism and momentum based hippocampal shape discrimination in dementia of the Alzheimer type, IEEE Transactions on Medical Imaging, vol.26, issue.4, p.462470, 2007.

X. F. Yang, A. Goh, and A. Qiu, Approximations of the dieomorphic metric and their applications in shape learning, Information Processing in Medical Imaging :IPMI, p.257270, 2011.