S. P. Awate, H. Zhang, and J. C. Gee, A Fuzzy, Nonparametric Segmentation Framework for DTI and MRI Analysis: With Applications to DTI-Tract Extraction, IEEE Transactions on Medical Imaging, vol.26, issue.11, pp.1525-1536, 2007.
DOI : 10.1109/TMI.2007.907301

D. L. Bihan, J. Mangin, C. Poupon, C. A. Clark, S. Pappata et al., Diffusion tensor imaging: Concepts and applications, Journal of Magnetic Resonance Imaging, vol.44, issue.4, pp.534-546, 2001.
DOI : 10.1002/jmri.1076
URL : https://hal.archives-ouvertes.fr/hal-00349820

A. Brun, H. Knutsson, H. J. Park, M. E. Shenton, and C. Westin, Clustering fiber tracts using normalized cuts, MICCAI, 2004.

V. De-silva and J. B. Tenenbaum, Global versus local methods in nonlinear dimensionality reduction, NIPS, pp.705-712, 2002.

Y. Duan, X. Li, and Y. Xi, Thalamus segmentation from diffusion tensor magnetic resonance imaging, Journal of Biomedical Imaging, issue.2 1, pp.1-1, 2007.

P. Fillard, N. Toussaint, and X. Pennec, Medinria: DT-MRI processing and visualization software, Similar Tensor Workshop, vol.5, p.7, 2006.

C. J. Galban, S. Maderwald, K. Uffmann, A. De-greiff, and M. E. Ladd, Diffusive sensitivity to muscle architecture: a magnetic resonance diffusion tensor imaging study of the human calf, European Journal of Applied Physiology, vol.227, issue.3, pp.253-262, 2004.
DOI : 10.1007/s00421-004-1186-2

B. Glocker, N. Komodakis, G. Tziritas, N. Navab, and N. Paragios, Dense image registration through MRFs and efficient linear programming???, Medical Image Analysis, vol.12, issue.6, pp.731-741, 2008.
DOI : 10.1016/j.media.2008.03.006

A. Goh and R. Vidal, Segmenting Fiber Bundles in Diffusion Tensor Images, ECCV, 2008.
DOI : 10.1007/978-3-540-88690-7_18

D. Haussler, Convolution kernels on discrete structures, 1999.

T. Jebara, R. Kondor, and A. Howard, Probability product kernels, Journal of Machine Learning Research, vol.5, issue.2, pp.819-844, 2004.

L. Jonasson, P. Hagmann, C. Pollo, X. Bresson, C. Wilson et al., A level set method for segmentation of the thalamus and its nuclei in DT-MRI, Signal Processing, vol.87, issue.2, pp.309-321, 2007.
DOI : 10.1016/j.sigpro.2005.12.017

C. Lenglet, M. Rousson, and R. Deriche, DTI segmentation by statistical surface evolution, IEEE Transactions on Medical Imaging, vol.25, issue.6, pp.685-700, 2006.
DOI : 10.1109/TMI.2006.873299
URL : https://hal.archives-ouvertes.fr/inria-00070183

M. Maddah, W. Grimson, S. Warfield, and W. Wells, A unified framework for clustering and quantitative analysis of white matter fiber tracts, Medical Image Analysis, vol.12, issue.2, pp.191-202, 2008.
DOI : 10.1016/j.media.2007.10.003

M. Maddah, A. U. Mewes, S. Haker, W. E. Grimson, and S. K. Warfield, Automated Atlas-Based Clustering of White Matter Fiber Tracts from DTMRI, MICCAI, p.5, 2005.
DOI : 10.1007/11566465_24

J. Melonakos, V. Mohan, M. Niethammer, K. Smith, A. Kubicki et al., Finsler Tractography for White Matter Connectivity Analysis of the Cingulum Bundle, 2007.
DOI : 10.1007/978-3-540-75757-3_5

N. Milne, Human functional anatomy 213

R. Neji, A. Besbes, N. Komodakis, J. Deux, M. Maatouk et al., Clustering of the Human Skeletal Muscle Fibers Using Linear Programming and Angular Hilbertian Metrics, IPMI, 2009.
DOI : 10.1007/978-3-540-88693-8_52
URL : https://hal.archives-ouvertes.fr/hal-00424532

L. Odonnell and C. Westin, White Matter Tract Clustering and Correspondence in Populations, MICCAI, 2005. 1
DOI : 10.1007/11566465_18

L. Odonnell and C. Westin, Automatic Tractography Segmentation Using a High-Dimensional White Matter Atlas, IEEE Transactions on Medical Imaging, vol.26, issue.11, pp.1562-1575, 2007.
DOI : 10.1109/TMI.2007.906785

X. Pennec, P. Fillard, and N. Ayache, A Riemannian Framework for Tensor Computing, International Journal of Computer Vision, vol.6, issue.2, pp.41-66, 2006.
DOI : 10.1007/s11263-005-3222-z
URL : https://hal.archives-ouvertes.fr/inria-00070743

P. Savadjiev, J. S. Campbell, G. B. Pike, and K. Siddiqi, Streamline Flows for White Matter Fibre Pathway Segmentation in Diffusion MRI, MICCAI, 2008.
DOI : 10.1007/978-3-540-85988-8_17

B. Scholkopf, A. Smola, and K. Muller, Nonlinear Component Analysis as a Kernel Eigenvalue Problem, Neural Computation, vol.20, issue.5, pp.1299-1319, 1998.
DOI : 10.1007/BF02281970

J. B. Tenenbaum, V. De-silva, and J. C. Langford, A Global Geometric Framework for Nonlinear Dimensionality Reduction, Science, vol.290, issue.5500, pp.2319-2323, 2000.
DOI : 10.1126/science.290.5500.2319

A. Tsai, C. Westin, A. O. Hero, and A. S. Willsky, Fiber Tract Clustering on Manifolds With Dual Rooted-Graphs, 2007 IEEE Conference on Computer Vision and Pattern Recognition, 2007.
DOI : 10.1109/CVPR.2007.383096

Y. Tsin, Kernel Correlation as an Affinity Measure in Point- Sampled Vision Problems, 2003.

V. Vapnik, Statistical Learning Theory, 1998.

Z. Wang and B. C. Vemuri, DTI segmentation using an information theoretic tensor dissimilarity measure, IEEE TMI, vol.24, issue.10 1, pp.1267-1277, 2005.

Y. T. Weldeselassie and G. Hamarneh, DT-MRI segmentation using graph cuts, SPIE Medical Imaging, issue.1, 2007.

U. Ziyan, D. Tuch, and C. Westin, Segmentation of Thalamic Nuclei from DTI Using Spectral Clustering, MICCAI, 2006.
DOI : 10.1007/11866763_99