J. R. Jensen et al., Introductory digital image processing: A remote sensing perspective. Prentice-Hall Inc., 1996, no. Ed. 2.
P. Basser, J. Mattiello, and D. L. Bihan, "MR diffusion tensor spectroscopy and imaging, " Biophysical Journal, vol. 66, no. 1, pp. 259 - 267, 1994.
M. H. Chappell, J. A. Brown, J. C. Dalrymple-Alford, A. M. Ulug, and R. Watts, "Multivariate analysis of diffusion tensor imaging data improves the detection of microstructural damage in young professional boxers, " Magn Reson Imaging, vol. 26, no. 10, pp. 1398- 405, 2008.
S. Chung, D. Pelletier, M. Sdika, Y. Lu, J. I. Berman, and R. G. Henry, "Whole brain voxel-wise analysis of single-subject serial DTI by permutation testing, " Neuroimage, vol. 39, no. 4, pp. 1693-705, 2008.
D. K. Jones, M. R. Symms, M. Cercignani, and R. J. Howard, "The effect of filter size on VBM analyses of DT-MRI data, " Neuroimage, vol. 26, no. 2, pp. 546-54, 2005.
C. B. Goodlett, P. T. Fletcher, J. H. Gilmore, and G. Gerig, "Group analysis of DTI fiber tract statistics with application to neurodevelopment, " Neuroimage, vol. 45, no. 1 Suppl, pp. 133-42, 2009.
A. D. Lee, N. Lepore, F. Lepore, F. Alary, P. Voss, Y. Chou, C. Brun, M. Barysheva, A. W. Toga, and P. M. Thompson, "Brain differences visualized in the blind using tensor manifold statistics and diffusion tensor imaging, " in Frontiers in the Convergence of Bioscience and Information Technologies, 2007. FBIT 2007. IEEE, 2007, pp. 470- 476.
A.-L. Fouque, P. Fillard, A. Bargiacchi, A. Cachia, M. Zilbovicius, B. Thyreau, E. Le Floch, P. Ciuciu, and E. Duchesnay, "Voxelwise multivariate statistics and brain-wide machine learning using the full diffusion tensor, " Med Image Comput Comput Assist Interv, vol. 14, no. Pt 2, pp. 9-16, 2011.
A. Grigis, V. Noblet, F. Heitz, F. Blanc, J. de Seze, S. Kremer, L. Rumbach, and J.-P. Armspach, "Longitudinal change detection in diffusion MRI using multivariate statistical testing on tensors, " Neuroimage, vol. 60, no. 4, pp. 2206-21, 2012.
X. Pennec, "Intrinsic statistics on Riemannian manifolds: Basic tools for geometric measurements, " Journal of Mathematical Imaging and Vision, vol. 25, no. 1, pp. 127-154, 2006.
P. T. Fletcher and S. Joshi, "Riemannian Geometry for the Statistical Analysis of Diffusion Tensor Data, " Signal Processing, vol. 87, pp. 250-262, 2007.
C. Lenglet, M. Rousson, R. Deriche, and O. Faugeras, "Statistics on the manifold of multivariate normal distributions: Theory and application to diffusion tensor MRI processing, " Journal of Mathematical Imaging and Vision, vol. 25, pp. 423-444, 2006.
I. L. Dryden, A. Koloydenko, and D. Zhou, "Non-Euclidean statistics for covariance matrices, with applications to diffusion tensor imaging, " The Annals of Applied Statistics, vol. 3, no. 3, pp. 1102-1123, 2009.
A. Schwartzman, R. F. Dougherty, and J. E. Taylor, "Group comparison of eigenvalues and eigenvectors of diffusion tensors, " Journal of the American Statistical Association, vol. 105, no. 490, pp. 588-599, 2010.
B. Whitcher, J. J. Wisco, N. Hadjikhani, and D. S. Tuch, "Statistical group comparison of diffusion tensors via multivariate hypothesis testing, " Magn Reson Med, vol. 57, no. 6, pp. 1065-74, 2007.
K. J. Friston, J. T. Ashburner, S. J. Kiebel, T. E. Nichols, and W. D. Penny, Statistical Parametric Mapping: The Analysis of Functional Brain Images. Academic Press, 2007.
T. Nichols and A. Holmes, "Nonparametric permutation tests for functional neuroimaging: A primer with examples, " Human brain mapping, vol. 15, no. 1, pp. 1-25, 2002.
P.-A. Absil, R. Mahony, and R. Sepulchre, "Riemannian geometry of Grassmann manifolds with a view on algorithmic computation, " Acta Applicandae Mathematicae, vol. 80, no. 2, pp. 199-220, 2004.
X. Pennec, P. Fillard, and N. Ayache, "A Riemannian framework for tensor computing, " International Journal of Computer Vision, vol. 66, no. 1, pp. 41-66, 2006.
S. Bonnabel and R. Sepulchre, "Riemannian metric and geometric mean for positive semidefinite matrices of fixed rank, " SIAM Journal on Matrix Analysis and Applications, vol. 31, no. 3, pp. 1055-1070, 2009.
V. Arsigny, P. Fillard, X. Pennec, and N. Ayache, "Log-Euclidean metrics for fast and simple calculs on diffusion tensors, " Magnetic Resonance in Medicine, vol. 56, pp. 411-421, 2006.
A. Collard, S. Bonnabel, C. Phillips, and R. Sepulchre, "An anisotropy preserving metric for DTI processing, " submitted to International Journal of Computer Vision, 2012.
P.W. Mielke and K. J. Berry, Permutation methods: A distance function approach. Springer Verlag, 2001.
F. Pesarin, Multivariate Permutation Tests : With Applications in Biostatistics. Wiley, 2001.
H. Boisgontier, V. Noblet, F. Heitz, L. Rumbach, and J.-P. Armspach, "Generalized likelihood ratio tests for change detection in diffusion tensor images: Application to multiple sclerosis, " Medical Image Analysis, vol. 16, no. 1, pp. 325-338, 2012.
