S. Allassonnière, A. Trouvé, and L. Younes, Geodesic Shooting and Diffeomorphic Matching Via Textured Meshes, Proc. of EMM- CVPR, pp.365-381, 2005.
DOI : 10.1007/11585978_24

S. Allassonnière, Y. Amit, and A. Trouvé, Towards a coherent statistical framework for dense deformable template estimation, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.5, issue.1, pp.3-29, 2007.
DOI : 10.1111/j.1467-9868.2007.00574.x

S. Allassonnière, E. Kuhn, and A. Trouvé, Construction of Bayesian deformable models via a stochastic approximation algorithm: A convergence study, Bernoulli, vol.16, issue.3, pp.641-678, 2010.
DOI : 10.3150/09-BEJ229

V. Arsigny, O. Commowick, X. Pennec, and N. Ayache, A logeuclidean framework for statistics on diffeomorphisms, Proc. MICCAI, pp.924-931, 2006.
URL : https://hal.archives-ouvertes.fr/inria-00615594

A. Beck and M. Teboulle, A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems, SIAM Journal on Imaging Sciences, vol.2, issue.1, pp.183-202, 2009.
DOI : 10.1137/080716542

M. Beg, M. Miller, A. Trouvé, and L. Younes, Computing Large Deformation Metric Mappings via Geodesic Flows of Diffeomorphisms, International Journal of Computer Vision, vol.61, issue.2, pp.139-157, 2005.
DOI : 10.1023/B:VISI.0000043755.93987.aa

T. Cootes, G. Edwards, and C. Taylor, Active appearance models, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.23, issue.6, pp.681-685, 2001.
DOI : 10.1109/34.927467

P. Dupuis, U. Grenander, and M. Miller, Variational problems on flows of diffeomorphisms for image matching, Quarterly of Applied Mathematics, vol.56, issue.3, pp.587-600, 1998.
DOI : 10.1090/qam/1632326

S. Durrleman, Statistical models of currents for measuring the variability of anatomical curves, surfaces and their evolution, Thèse de sciences, 2010.
URL : https://hal.archives-ouvertes.fr/tel-00631382

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, pp.793-808, 2009.
DOI : 10.1016/j.media.2009.07.007
URL : https://hal.archives-ouvertes.fr/hal-00816051

S. Durrleman, P. Fillard, X. Pennec, and A. Trouvé, Registration, atlas estimation and variability analysis of white matter fiber bundles modeled as currents, NeuroImage, vol.55, issue.3, pp.1073-1090
DOI : 10.1016/j.neuroimage.2010.11.056
URL : https://hal.archives-ouvertes.fr/hal-00816044

S. Durrleman, M. Prastawa, G. Gerig, and S. Joshi, Optimal datadriven sparse parameterization of diffeomorphisms for population analysis, Information Processing in Medical Imaging (IPMI), pp.123-134, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00818405

C. Glasbey and K. Mardia, A penalized likelihood approach to image warping, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.63, issue.3, pp.465-492, 2001.
DOI : 10.1111/1467-9868.00295

J. Glaunès, A. Qiu, M. Miller, and L. Younes, Large Deformation Diffeomorphic Metric Curve Mapping, International Journal of Computer Vision, vol.13, issue.2, pp.317-336, 2008.
DOI : 10.1007/s11263-008-0141-9

U. Grenander, General Pattern Theory: a Mathematical Theory of Regular Structures Computational anatomy: An emerging discipline, Quarterly of Applied Mathematics LVI, issue.4, pp.617-694, 1994.

U. Grenander, A. Srivastava, and S. Saini, A Pattern-Theoretic Characterization of Biological Growth, IEEE Transactions on Medical Imaging, vol.26, issue.5, pp.648-659, 2007.
DOI : 10.1109/TMI.2006.891500

M. Hansen, R. Larsen, B. Glocker, and N. Navab, Adaptive parametrization of multivariate B-splines for image registration, 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp.1-8, 2008.
DOI : 10.1109/CVPR.2008.4587760

T. Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2009.

S. Joshi and M. Miller, Landmark matching via large deformation diffeomorphisms, IEEE Transactions on Image Processing, vol.9, issue.8, pp.1357-1370, 2000.
DOI : 10.1109/83.855431

W. Lei, F. Beg, T. Ratnanather, C. Ceritoglu, L. Younes et al., Large deformation diffeomorphism and momentum based hippocampal shape discrimination in dementia of the alzheimer type, IEEE Trans on Medical Imaging, vol.26, pp.462-470, 2007.

P. Lorenzen, B. Davis, and S. Joshi, Unbiased Atlas Formation Via Large Deformations Metric Mapping, Lecture Notes in Computer Science, vol.3750, pp.411-418, 2005.
DOI : 10.1007/11566489_51

S. Marsland and R. Mclachlan, A Hamiltonian Particle Method for Diffeomorphic Image Registration, Proceedings of Information Processing in Medical Imaging (IPMI), pp.396-407, 2007.
DOI : 10.1007/978-3-540-73273-0_33

Y. Meyer, Oscillating patterns in image processing and nonlinear evolution equations Providence, RI, the fifteenth Dean Jacqueline B. Lewis memorial lectures Miller I M, Trouvé A, Younes L (2002) On the metrics and eulerlagrange equations of computational anatomy, Annual Review of Biomedical Engineering, vol.22, issue.4, pp.375-405, 2001.

M. Miller and L. Younes, Group actions, homeomorphisms, and matching: A general framework, International Journal of Computer Vision, vol.41, issue.1/2, pp.61-84, 2001.
DOI : 10.1023/A:1011161132514

M. Miller, A. Trouvé, and L. Younes, Geodesic Shooting for Computational Anatomy, Journal of Mathematical Imaging and Vision, vol.13, issue.1???2, pp.209-228, 2006.
DOI : 10.1007/s10851-005-3624-0

Y. Nesterov, A method of solving a convex programming problem with convergence rate A Riemannian framework for tensor computing, Soviet Math Dokl International Journal of Computer Vision, vol.27, issue.661, pp.41-66, 1983.

L. Risser, F. Vialard, R. Wolz, M. Murgasova, D. Holm et al., Simultaneous Multi-scale Registration Using Large Deformation Diffeomorphic Metric Mapping, IEEE Transactions on Medical Imaging, vol.30, issue.10, pp.1746-1759, 2011.
DOI : 10.1109/TMI.2011.2146787

D. Rueckert, P. Aljabar, R. Heckemann, J. Hajnal, and A. Hammers, Diffeomorphic Registration Using B-Splines, Proc. MICCAI, pp.702-709, 2006.
DOI : 10.1007/11866763_86

N. Singh, P. Fletcher, J. Preston, L. Ha, R. King et al., Multivariate Statistical Analysis of Deformation Momenta Relating Anatomical Shape to Neuropsychological Measures, Proc. MICCAI'10, pp.529-537, 2010.
DOI : 10.1007/978-3-642-15711-0_66

S. Sommer, M. Nielsen, S. Darkner, and X. Pennec, Higher order kernels and locally affine lddmm registration ArXiv:1112, pp.3166-3167, 2012.

S. Sommer, M. Nielsen, and X. Pennec, Sparsity and scale: Compact representations of deformation for diffeomorphic registration, 2012 IEEE Workshop on Mathematical Methods in Biomedical Image Analysis, 2012.
DOI : 10.1109/MMBIA.2012.6164753
URL : https://hal.archives-ouvertes.fr/hal-00641357

A. Trouvé, Diffeomorphisms groups and pattern matching in image analysis, International Journal of Computer Vision, vol.28, issue.3, pp.213-221, 1998.
DOI : 10.1023/A:1008001603737

A. Trouvé and L. Younes, Metamorphoses Through Lie Group Action, Foundations of Computational Mathematics, vol.5, issue.2, pp.173-198, 2005.
DOI : 10.1007/s10208-004-0128-z

M. Vaillant and J. Glaunès, Surface Matching via Currents, Proceedings of Information Processing in Medical Imaging, pp.381-392, 2005.
DOI : 10.1007/11505730_32
URL : https://hal.archives-ouvertes.fr/hal-00263652

M. Vaillant, M. Miller, L. Younes, and A. Trouvé, Statistics on diffeomorphisms via tangent space representations, NeuroImage, vol.23, pp.161-169, 2004.
DOI : 10.1016/j.neuroimage.2004.07.023

T. Vercauteren, X. Pennec, A. Perchant, and N. Ayache, Diffeomorphic demons: Efficient non-parametric image registration, NeuroImage, vol.45, issue.1, pp.61-72, 2009.
DOI : 10.1016/j.neuroimage.2008.10.040
URL : https://hal.archives-ouvertes.fr/inserm-00349600

G. Yu, G. Sapiro, and S. Mallat, Image modeling and enhancement via structured sparse model selection, 2010 IEEE International Conference on Image Processing, pp.1641-1644, 2010.
DOI : 10.1109/ICIP.2010.5653853

H. Zou and T. Hastie, Regularization and variable selection via the elastic net, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.5, issue.2, pp.301-320, 2005.
DOI : 10.1073/pnas.201162998