Sapiro : ODF reconstruction in Q-ball imaging with solid angle consideration, IEEE Internaional Symposium on Biomedical Imaging, pp.1398-1401, 2009. ,
Composite hindered and restricted model of diffusion (CHARMED) MR imaging of the human brain, NeuroImage, vol.27, issue.1, pp.48-58, 2005. ,
DOI : 10.1016/j.neuroimage.2005.03.042
Regularized positive-definite fourth order tensor field estimation from DW-MRI, NeuroImage, vol.45, issue.1, pp.153-162, 2009. ,
DOI : 10.1016/j.neuroimage.2008.10.056
A unified framework for estimating diffusion tensors of any order with symmetric positive-definite constraints, 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.1385-1388, 2010. ,
DOI : 10.1109/ISBI.2010.5490256
Inferring microstructural features and the physiological state of tissues from diffusion-weighted images, NMR in Biomedicine, vol.34, issue.7, pp.333-344, 1995. ,
DOI : 10.1002/nbm.1940080707
Diffusion-tensor MRI: theory, experimental design and data analysis - a technical review, NMR in Biomedicine, vol.20, issue.7-8, pp.456-467, 2002. ,
DOI : 10.1002/nbm.783
Microstructural and Physiological Features of Tissues Elucidated by Quantitative-Diffusion-Tensor MRI, Journal of Magnetic Resonance, Series B, vol.111, issue.3, pp.209-219, 1996. ,
DOI : 10.1006/jmrb.1996.0086
The multidimensional moment problem and semigroups. Moments in mathematics, pp.110-124, 1987. ,
Diffusion orientation transform revisited, NeuroImage, vol.49, issue.2, pp.1326-1339, 2010. ,
DOI : 10.1016/j.neuroimage.2009.09.067
High Angular Resolution Diffusion MRI : From Local Estimation to Segmentation and Tractography, Thèse de doctorat, 2008. ,
URL : https://hal.archives-ouvertes.fr/tel-00457458
Deriche : A fast and robust ODF estimation algorithm in Q-ball imaging, IEEE International Symposium on Biomedical Imaging, pp.81-84, 2006. ,
Poupon : Diffusion propagator imaging : Using laplace's equation and multiple shell acquisitions to reconstruct the diffusion propagator, International Conference on Information Processing in Medical Imaging, pp.1-13, 2009. ,
Clinical DT-MRI Estimation, Smoothing, and Fiber Tracking With Log-Euclidean Metrics, IEEE Transactions on Medical Imaging, vol.26, issue.11, pp.1472-1482, 2007. ,
DOI : 10.1109/TMI.2007.899173
URL : https://hal.archives-ouvertes.fr/inria-00502645
Deriche : A polynomial based approach to extract the maxima of an antipodally symmetric spherical function and its application to extract fiber directions from the orientation distribution function in diffusion MRI, Medical Image Computing and Computer Assisted Intervention, Workshop on Computational Diffusion MRI, pp.237-248, 2008. ,
Ueber die Darstellung definiter Formen als Summe von Formenquadraten, Mathematische Annalen, vol.32, issue.3, pp.342-350, 1888. ,
DOI : 10.1007/BF01443605
Hessian sufficiency for bordered hessian, Research Letters in the Information and Mathematical Sciences, vol.8, pp.189-196, 2005. ,
A novel tensor distribution model for the diffusion-weighted MR signal, NeuroImage, vol.37, issue.1, pp.164-176, 2007. ,
DOI : 10.1016/j.neuroimage.2007.03.074
Optimal strategies for measuring diffusion in anisotropic systems by magnetic resonance imaging, Magnetic Resonance in Medicine, vol.8, issue.3, pp.515-525, 1999. ,
DOI : 10.1002/(SICI)1522-2594(199909)42:3<515::AID-MRM14>3.0.CO;2-Q
The propagator representation of molecular transport in microporous crystallites, Journal of Magnetic Resonance (1969), vol.51, issue.1, pp.1-7, 1983. ,
DOI : 10.1016/0022-2364(83)90094-X
Diffusion Tensor Estimation by Maximizing Rician Likelihood, 2007 IEEE 11th International Conference on Computer Vision, pp.1-8, 2007. ,
DOI : 10.1109/ICCV.2007.4409140
Solving Least Squares Problems, 1974. ,
DOI : 10.1137/1.9781611971217
Distortion correction and robust tensor estimation for MR diffusion imaging, Medical Image Analysis, vol.6, issue.3, pp.191-198, 2002. ,
DOI : 10.1016/S1361-8415(02)00079-8
URL : https://hal.archives-ouvertes.fr/hal-00349706
Physical foundations, models, and methods of diffusion magnetic resonance imaging of the brain: A review, Concepts in Magnetic Resonance Part A, pp.30-278, 2007. ,
DOI : 10.1002/cmr.a.20094
Visualization Techniques for Computational Mechanics, Thèse de doctorat, 2009. ,
Generalized diffusion tensor imaging and analytical relationships between diffusion tensor imaging and high angular resolution diffusion imaging, Magnetic Resonance in Medicine, vol.48, issue.5, pp.955-965, 2003. ,
DOI : 10.1002/mrm.10596
Resolution of complex tissue microarchitecture using the diffusion orientation transform (DOT), NeuroImage, vol.31, issue.3 ,
DOI : 10.1016/j.neuroimage.2006.01.024
Generalized scalar measures for diffusion MRI using trace, variance, and entropy, Magnetic Resonance in Medicine, vol.40, issue.4, pp.866-876, 2005. ,
DOI : 10.1002/mrm.20411
Pulsed-field gradient nuclear magnetic resonance as a tool for studying translational diffusion, part 1 : basic theory, Magnetic Resonance : an Educational Journal, vol.9, issue.5, pp.299-336, 1997. ,
Eigenvalues of a real supersymmetric tensor, Journal of Symbolic Computation, vol.40, issue.6, pp.1302-1324, 2005. ,
DOI : 10.1016/j.jsc.2005.05.007
Z-eigenvalue methods for a global polynomial optimization problem, Mathematical Programming, vol.23, issue.2, pp.301-316, 2009. ,
DOI : 10.1007/s10107-007-0193-6
<mml:math altimg="si6.gif" display="inline" overflow="scroll" xmlns:xocs="http://www.elsevier.com/xml/xocs/dtd" xmlns:xs="http://www.w3.org/2001/XMLSchema" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://www.elsevier.com/xml/ja/dtd" xmlns:ja="http://www.elsevier.com/xml/ja/dtd" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:tb="http://www.elsevier.com/xml/common/table/dtd" xmlns:sb="http://www.elsevier.com/xml/common/struct-bib/dtd" xmlns:ce="http://www.elsevier.com/xml/common/dtd" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:cals="http://www.elsevier.com/xml/common/cals/dtd"><mml:mi>D</mml:mi></mml:math>-eigenvalues of diffusion kurtosis tensors, Journal of Computational and Applied Mathematics, vol.221, issue.1, pp.150-157, 2008. ,
DOI : 10.1016/j.cam.2007.10.012
Sums of Squares of Polynomials, The American Mathematical Monthly, vol.107, issue.9, pp.813-821, 2000. ,
DOI : 10.2307/2695736
Formal characterization and extension of the linearized diffusion tensor model, Human Brain Mapping, vol.42, issue.2, pp.144-155, 2005. ,
DOI : 10.1002/hbm.20076
Estimating Crossing Fibers: A Tensor Decomposition Approach, IEEE Transactions on Visualization and Computer Graphics, vol.14, issue.6, pp.1635-1642, 2008. ,
DOI : 10.1109/TVCG.2008.128
Spin Diffusion Measurements: Spin Echoes in the Presence of a Time???Dependent Field Gradient, The Journal of Chemical Physics, vol.42, issue.1, pp.288-292, 1965. ,
DOI : 10.1063/1.1695690
The null information probability density for anisotropic tensors, 2000. ,
Direct estimation of the fiber orientation density function from diffusion-weighted MRI data using spherical deconvolution, NeuroImage, vol.23, issue.3, pp.1176-1185, 2004. ,
DOI : 10.1016/j.neuroimage.2004.07.037
Q-ball imaging, Magnetic Resonance in Medicine, vol.23, issue.6, pp.1358-1372, 2004. ,
DOI : 10.1002/mrm.20279
Mapping complex tissue architecture with diffusion spectrum magnetic resonance imaging, Magnetic Resonance in Medicine, vol.118, issue.6, pp.1377-1386, 2005. ,
DOI : 10.1002/mrm.20642
Symmetric Positive-Definite Cartesian Tensor Orientation Distribution Functions (CT-ODF), Medical Image Computing and Computer Assisted Intervention, pp.582-589, 2010. ,
DOI : 10.1007/978-3-642-15705-9_71
Processing and visualization for diffusion tensor MRI, Medical Image Analysis, vol.6, issue.2, pp.93-108, 2002. ,
DOI : 10.1016/S1361-8415(02)00053-1
Bonferroni and Sidak corrections for multiple comparisons, pp.103-107 ,
Elastic Matching of Diffusion Tensor Images, Computer Vision and Image Understanding, vol.77, issue.2, pp.233-250, 2000. ,
DOI : 10.1006/cviu.1999.0817
Spatial transformations of diffusion tensor magnetic resonance images, IEEE Transactions on Medical Imaging, vol.20, issue.11, pp.1131-1139, 2001. ,
DOI : 10.1109/42.963816
DETECTION OF GLIOMA EVOLUTION ON LONGITUDINAL MRI STUDIES, 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.49-52, 2007. ,
DOI : 10.1109/ISBI.2007.356785
Glioma Dynamics and Computational Models: A Review of Segmentation, Registration, and In Silico Growth Algorithms and their Clinical Applications, Current Medical Imaging Reviews, vol.3, issue.4, pp.262-276, 2007. ,
DOI : 10.2174/157340507782446241
URL : https://hal.archives-ouvertes.fr/inria-00616021
Ayache : Fast and simple calculus on tensors in the log-euclidean framework, Medical Image Computing and Computer Assisted Intervention, Palm Springs, pp.115-122, 2005. ,
Log-Euclidean metrics for fast and simple calculus on diffusion tensors, Magnetic Resonance in Medicine, vol.52, issue.2, pp.411-421, 2006. ,
DOI : 10.1002/mrm.20965
URL : https://hal.archives-ouvertes.fr/inria-00502678
A normal distribution for tensor-valued random variables: applications to diffusion tensor MRI, IEEE Transactions on Medical Imaging, vol.22, issue.7, pp.785-794, 2003. ,
DOI : 10.1109/TMI.2003.815059
Controlling the false discovery rate : a practical and powerful approach to multiple testing, Journal of the Royal Statistical Society series B-Methodological, vol.57, issue.1, pp.289-300, 1995. ,
The control of the false discovery rate in multiple testing under dependency, Annals of Statistics, vol.29, issue.4, pp.1165-1188, 2001. ,
Armspach : An automatic method for change detection in serial DTI-derived scalar images, Medical Détection de changements en IRM de diffusion Bibliographie Image Computing and Computer Assisted Intervention, 2008. ,
Generalized likelihood ratio tests for change detection in diffusion tensor images: Application to multiple sclerosis, Medical Image Analysis, vol.16, issue.1, pp.325-338, 2012. ,
DOI : 10.1016/j.media.2011.08.007
Automatic change detection in multimodal serial MRI: application to multiple sclerosis lesion evolution, NeuroImage, vol.20, issue.2, pp.643-656, 2003. ,
DOI : 10.1016/S1053-8119(03)00406-3
Diffeomorphic matching of diffusion tensor images, Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop, CVPRW '06, p.67, 2006. ,
The asymptotic distribution of diffusion tensor and fractional anisotropy estimates, Magnetic Resonance in Medicine, vol.16, issue.1, pp.2006-2006, 2006. ,
Statistics on special manifolds. Lecture notes in statistics, 2003. ,
Whole brain voxel-wise analysis of single-subject serial DTI by permutation testing, NeuroImage, vol.39, issue.4, pp.1693-1705, 2008. ,
DOI : 10.1016/j.neuroimage.2007.10.039
Diffusion-based tractography in neurological disorders: concepts, applications, and future developments, The Lancet Neurology, vol.7, issue.8, pp.715-727, 2008. ,
DOI : 10.1016/S1474-4422(08)70163-7
Fiber tract-oriented statistics for quantitative diffusion tensor MRI analysis, Medical Image Analysis, vol.10, issue.5, pp.786-798, 2006. ,
DOI : 10.1016/j.media.2006.07.003
URL : https://hal.archives-ouvertes.fr/inserm-00770970
Large-Scale Simultaneous Hypothesis Testing, Journal of the American Statistical Association, vol.99, issue.465, pp.96-104, 2004. ,
DOI : 10.1198/016214504000000089
Effects of signal-to-noise ratio on the accuracy and reproducibility of diffusion tensor imaging???derived fractional anisotropy, mean diffusivity, and principal eigenvector measurements at 1.5T, Journal of Magnetic Resonance Imaging, vol.34, issue.3, pp.756-767, 2007. ,
DOI : 10.1002/jmri.21053
Principal Geodesic Analysis on Symmetric Spaces: Statistics of Diffusion Tensors, European Conference on Computer Vision, Workshops CVAMIA and MMBIA, pp.87-98, 2004. ,
DOI : 10.1007/978-3-540-27816-0_8
Modeling Brain Deformations in Alzheimer Disease by Fluid Registration of Serial 3D MR Images, Journal of Computer Assisted Tomography, vol.22, issue.5, pp.838-843, 1998. ,
DOI : 10.1097/00004728-199809000-00031
Matrix variate distributions. Chapman & Hall/CRC monographs and surveys in pure and applied mathematics, 2000. ,
Tract probability maps in stereotaxic spaces: Analyses of white matter anatomy and tract-specific quantification, NeuroImage, vol.39, issue.1, pp.336-347, 2008. ,
DOI : 10.1016/j.neuroimage.2007.07.053
Kernel-Based Manifold Learning for Statistical Analysis of Diffusion Tensor Images, International Conference on Information Processing in Medical Imaging, pp.581-593, 2007. ,
DOI : 10.1007/978-3-540-73273-0_48
The detection and significance of subtle changes in mixed-signal brain lesions by serial MRI scan matching and spatial normalization, Medical Image Analysis, vol.2, issue.3, pp.227-242, 1998. ,
DOI : 10.1016/S1361-8415(98)80021-2
Longitudinal diffusion tensor imaging in a rat brain glioma model, NMR in Biomedicine, vol.20, issue.4, pp.799-808, 2008. ,
DOI : 10.1002/nbm.1256
Wells : A mathematical framework for incorporating anatomical knowledge in DT-MRI analysis, IEEE International Symposium on Biomedical Imaging, pp.105-108, 2008. ,
Nonparametric permutation tests for functional neuroimaging: A primer with examples, Human Brain Mapping, vol.4, issue.1, pp.1-25, 2002. ,
DOI : 10.1002/hbm.1058
Robust voxel similarity metrics for the registration of dissimilar single and multimodal images, Pattern Recognition, vol.32, issue.8, pp.1349-1366, 1999. ,
DOI : 10.1016/S0031-3203(98)00167-8
Recalage non rigide d'images cérébrales 3D avec contrainte de conservation de la topologie, Thèse de doctorat, 2006. ,
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
Multivariate analysis of diffusion tensor data using hotelling T2 statistic, In International Society for Magnetic Resonance in Medicine, p.1324, 2005. ,
T1 hypointense lesion load in secondary progressive multiple sclerosis: a comparison of pre versus post contrast loads and of manual versus semi automated threshold techniques for lesion segmentation, Multiple Sclerosis, vol.4, issue.5, pp.408-412, 1998. ,
DOI : 10.1191/135245898678919483
Parametric and non-parametric statistical analysis of DT-MRI data, Journal of Magnetic Resonance, vol.161, issue.1, pp.1-14, 2002. ,
DOI : 10.1016/S1090-7807(02)00178-7
Part 1. Automated Change Detection and Characterization in Serial MR Studies of Brain-Tumor Patients, Journal of Digital Imaging, vol.11, issue.3, pp.203-222, 2007. ,
DOI : 10.1007/s10278-006-1038-1
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
Diffusion Tensor Imaging of Brain Tumours at 3T: A Potential Tool for Assessing White Matter Tract Invasion?, Magnetic Resonance : an Educational Journal, pp.455-462299, 1997. ,
DOI : 10.1016/S0009-9260(03)00115-6
Automatic detection and segmentation of evolving processes in 3D medical images: Application to multiple sclerosis, Medical Image Analysis, vol.6, issue.2, pp.163-179, 2002. ,
DOI : 10.1016/S1361-8415(02)00056-7
URL : https://hal.archives-ouvertes.fr/inria-00615024
Roysam : Image change detection algorithms : a systematic survey, IEEE Transactions on Image Process, vol.14, issue.3, pp.294-307, 2005. ,
Comparaison d'images : analyse longitudinale In Ecole de printemps, ANGD CNRS, Traitement des images m ? A c dicales : du voxel aux atlas, 2008. ,
An a contrario approach for change detection in 3D multimodal images : Application to multiple sclerosis in MRI, In IEEE Engineering in Medicine and Biology Society, pp.2069-2072, 2007. ,
Detection of tumour infiltration in axonal fibre bundles using diffusion tensor imaging, The International Journal of Medical Robotics and Computer Assisted Surgery, vol.20, issue.3, pp.80-86, 2005. ,
DOI : 10.1002/rcs.31
Random ellipsoids and false discovery rates : statistics for diffusion tensor imaging data, Thèse de doctorat, 2006. ,
Cross-subject comparison of principal diffusion direction maps, Magnetic Resonance in Medicine, vol.28, issue.6, pp.1423-1431, 2005. ,
DOI : 10.1002/mrm.20503
Group Comparison of Eigenvalues and Eigenvectors of Diffusion Tensors, Journal of the American Statistical Association, vol.105, issue.490, pp.588-599, 2010. ,
DOI : 10.1198/jasa.2010.ap07291
Inference for eigenvalues and eigenvectors of Gaussian symmetric matrices, The Annals of Statistics, vol.36, issue.6, pp.2886-2919, 2009. ,
DOI : 10.1214/08-AOS628
Slump : Change detection and classification in brain MR images using Change Vector Analysis, In IEEE Engineering in Medicine and Biology Society, issue.11, pp.7803-7807, 2011. ,
Ayache et X. Pennec : Non-rigid atlas to subject registration with pathologies for conformal brain radiotherapy, Medical Image Computing and Computer Assisted Intervention, Palm Springs, pp.704-711, 2005. ,
Diffusion tensor imaging in primary brain tumors : reproducible quantitative analysis of corpus callosum infiltration and contralateral involvement using a probabilistic mixture model, Neuroimage, issue.2, pp.31531-542, 2006. ,
A direct approach to false discovery rates, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.82, issue.3, pp.479-498, 2002. ,
DOI : 10.1111/1467-9868.00346
Dense feature deformation morphometry: Incorporating DTI data into conventional MRI morphometry, Medical Image Analysis, vol.12, issue.6, pp.742-751, 2008. ,
DOI : 10.1016/j.media.2008.03.010
Deformation analysis to detect and quantify active lesions in three-dimensional medical image sequences, IEEE Transactions on Medical Imaging, vol.18, issue.5, pp.429-441, 1999. ,
DOI : 10.1109/42.774170
URL : https://hal.archives-ouvertes.fr/inria-00615095
Contribution of diffusion tensor imaging to delineation of gliomas and glioblastomas, Journal of Magnetic Resonance Imaging, vol.177, issue.6, pp.905-912, 2004. ,
DOI : 10.1002/jmri.20217
On Analyzing Diffusion Tensor Images by Identifying Manifold Structure Using Isomaps, IEEE Transactions on Medical Imaging, vol.26, issue.6, pp.772-778, 2007. ,
DOI : 10.1109/TMI.2006.891484
Davsatzikos : Manifold Based Morphometry applied to schizophrenia, IEEE International Symposium on Biomedical Imaging, pp.704-707, 2008. ,
Statistical group comparison of diffusion tensors via multivariate hypothesis testing, Magnetic Resonance in Medicine, vol.127, issue.6, pp.1065-1074, 2007. ,
DOI : 10.1002/mrm.21229
A unified statistical approach for determining significant signals in images of cerebral activation, Human Brain Mapping, vol.12, issue.1, pp.58-73, 1996. ,
DOI : 10.1002/(SICI)1097-0193(1996)4:1<58::AID-HBM4>3.0.CO;2-O
Clatz : Dti registration with exact finite-strain differential, IEEE International Symposium on Biomedical Imaging, pp.700-703, 2008. ,
A Comparative Study of Biomechanical Simulators in Deformable Registration of Brain Tumor Images, IEEE Transactions on Biomedical Engineering, vol.55, issue.3, pp.1233-1236, 2008. ,
DOI : 10.1109/TBME.2007.905484
ORBIT: A Multiresolution Framework for Deformable Registration of Brain Tumor Images, IEEE Transactions on Medical Imaging, vol.27, issue.8, pp.1003-1017, 2008. ,
DOI : 10.1109/TMI.2008.916954
Spatial transformations of diffusion tensor magnetic resonance images, IEEE Transactions on Medical Imaging, vol.20, issue.11, pp.1131-1139, 2001. ,
DOI : 10.1109/42.963816
Geometric Means in a Novel Vector Space Structure on Symmetric Positive???Definite Matrices, SIAM Journal on Matrix Analysis and Applications, vol.29, issue.1, pp.328-347, 2007. ,
DOI : 10.1137/050637996
URL : https://hal.archives-ouvertes.fr/inria-00616031
In vivo fiber tractography using DT-MRI data, Magnetic Resonance in Medicine, vol.40, issue.4, pp.625-632, 2000. ,
DOI : 10.1002/1522-2594(200010)44:4<625::AID-MRM17>3.0.CO;2-O
Probabilistic diffusion tractography with multiple fibre orientations: What can we gain?, NeuroImage, vol.34, issue.1, pp.144-155, 2007. ,
DOI : 10.1016/j.neuroimage.2006.09.018
Automatic change detection in multimodal serial MRI: application to multiple sclerosis lesion evolution, NeuroImage, vol.20, issue.2, pp.643-656, 2003. ,
DOI : 10.1016/S1053-8119(03)00406-3
Westin : Clustering fiber traces using normalized cuts, Medical Image Computing and Computer Assisted Intervention, Saint-Malo, pp.368-375, 2004. ,
Flow-based fiber tracking with diffusion tensor and q-ball data: Validation and comparison to principal diffusion direction techniques, NeuroImage, vol.27, issue.4, pp.725-736, 2005. ,
DOI : 10.1016/j.neuroimage.2005.05.014
Bootstrap methods : a guide for practitioners and researchers, 2007. ,
Comparison of bootstrap approaches for estimation of uncertainties of DTI parameters, NeuroImage, vol.33, issue.2, pp.531-541, 2006. ,
DOI : 10.1016/j.neuroimage.2006.07.001
Towards a shape model of white matter fiber bundles using diffusion tensor MRI, 2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano (IEEE Cat No. 04EX821), pp.344-347, 2004. ,
DOI : 10.1109/ISBI.2004.1398545
URL : https://hal.archives-ouvertes.fr/inserm-00772619
Classification and quantification of neuronal fiber pathways using diffusion tensor MRI, Magnetic Resonance in Medicine, vol.12, issue.4, pp.716-7211218, 1981. ,
DOI : 10.1002/mrm.10415
A Bayesian approach for stochastic white matter tractography, IEEE Transactions on Medical Imaging, vol.25, issue.8, pp.965-978, 2006. ,
DOI : 10.1109/TMI.2006.877093
Fast dimensionality reduction for brain tractography clustering, 16th Annual Meeting of the Organization for Human Brain Mapping, 2010. ,
On averaging rotations, International Journal of Computer Vision, vol.42, issue.1/2, pp.7-16, 2001. ,
DOI : 10.1023/A:1011129215388
Armspach : On the integration of spatial neighborhood information for detecting longitudinal changes in mri sequences, LIVIM, 2011. ,
Twenty-five pitfalls in the analysis of diffusion MRI data, NMR in Biomedicine, vol.2, issue.7, pp.803-820, 2010. ,
DOI : 10.1002/nbm.1543
Bootstrap white matter tractography (BOOT-TRAC), NeuroImage, vol.24, issue.2 ,
DOI : 10.1016/j.neuroimage.2004.08.050
Probabilistic Clustering and Quantitative Analysis of White Matter Fiber Tracts, Information Processing in Medical Imaging, pp.372-383, 2007. ,
DOI : 10.1007/978-3-540-73273-0_31
Evaluation of fiber clustering methods for diffusion tensor imaging, IEEE International Conference on Information Visualization, pp.65-72, 2005. ,
Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging, Annals of Neurology, vol.40, issue.2, pp.265-269, 1999. ,
DOI : 10.1002/1531-8249(199902)45:2<265::AID-ANA21>3.0.CO;2-3
Retrospective evaluation of a topology preserving non-rigid registration method, Medical Image Analysis, vol.10, issue.3, pp.366-384, 2006. ,
DOI : 10.1016/j.media.2006.01.001
Westin : White matter tract clustering and correspondence in populations, Medical Image Computing and Computer Assisted Intervention, Palm Springs, pp.140-147, 2005. ,
Westin : High-dimensional white matter atlas generation and group analysis, Medical Image Computing and Computer Assisted Intervention, Copenhage, pp.243-251, 2006. ,
Parametric and non-parametric statistical analysis of DT-MRI data, Journal of Magnetic Resonance, vol.161, issue.1, pp.1-14, 2002. ,
DOI : 10.1016/S1090-7807(02)00178-7
Probabilistic Monte Carlo Based Mapping of Cerebral Connections Utilising Whole-Brain Crossing Fibre Information, Information Processing in Medical Imaging, pp.684-695, 2003. ,
DOI : 10.1007/978-3-540-45087-0_57
Computing the mean of geometric features : Application to the mean rotation, Institut National de Recherche en Informatique et en Automatique, 1998. ,
URL : https://hal.archives-ouvertes.fr/inria-00073318
Probabilistic Tractography Using Q-Ball Modeling and Particle Filtering, Medical Image Computing and Computer Assisted Intervention, pp.209-216, 2011. ,
DOI : 10.1016/j.media.2008.05.001
Diffusion MRI of Complex Neural Architecture, Neuron, vol.40, issue.5, pp.885-895, 2003. ,
DOI : 10.1016/S0896-6273(03)00758-X
Using the wild bootstrap to quantify uncertainty in diffusion tensor imaging, Human Brain Mapping, vol.48, issue.3, pp.346-362, 2008. ,
DOI : 10.1002/hbm.20395
Identifying White-Matter Fiber Bundles in DTI Data Using an Automated Proximity-Based Fiber-Clustering Method, IEEE Transactions on Visualization and Computer Graphics, vol.14, issue.5, pp.1044-1053, 2008. ,
DOI : 10.1109/TVCG.2008.52
Neuromy??lite optique de Devic, troubles cognitifs et imagerie c??r??brale par r??sonance magn??tique, Thèse de doctorat, 2010. ,
DOI : 10.1016/S0035-3787(11)70006-6
Generalized likelihood ratio tests for change detection in diffusion tensor images: Application to multiple sclerosis, Medical Image Analysis, vol.16, issue.1, pp.325-338, 2012. ,
DOI : 10.1016/j.media.2011.08.007
Neuromyelitis optica in France: A multicenter study of 125 patients, Neurology, vol.74, issue.9, pp.736-742, 2010. ,
DOI : 10.1212/WNL.0b013e3181d31e35
La BCcogSEP : une batterie courte d?????valuation des fonctions cognitives destin??es aux patients souffrant de scl??rose en plaques, Revue Neurologique, vol.160, issue.1, pp.51-62, 2004. ,
DOI : 10.1016/S0035-3787(04)70847-4
An introduction to ROC analysis, Pattern Recognition Letters, vol.27, issue.8, pp.861-874, 2006. ,
DOI : 10.1016/j.patrec.2005.10.010
Brain dysmyelination and recovery assessment by noninvasive in vivo diffusion tensor magnetic resonance imaging, Journal of Neuroscience Research, vol.20, issue.2, pp.392-402, 2006. ,
DOI : 10.1002/jnr.20742
Cognitive impairment and whole brain diffusion in patients with neuromyelitis optica after acute relapse, Brain and Cognition, vol.77, issue.1, pp.80-88, 2011. ,
DOI : 10.1016/j.bandc.2011.05.007
Rating neurologic impairment in multiple sclerosis: An expanded disability status scale (EDSS), Neurology, vol.33, issue.11, pp.1444-1452, 1983. ,
DOI : 10.1212/WNL.33.11.1444
Weinshenker : A serum autoantibody marker of neuromyelitis optica : distinction from multiple sclerosis, Lancet, issue.9451, pp.3642106-2112, 2004. ,
Detection and modeling of non-Gaussian apparent diffusion coefficient profiles in human brain data, Une possibilité pour détecter des changements d'orientations des fibres en considérant des tenseurs d, pp.331-340, 2002. ,
DOI : 10.1002/mrm.10209
Adaptive Kernels for Multi-fiber Reconstruction, International Conference on Information Processing in Medical Imaging, pp.338-349, 2009. ,
DOI : 10.1016/j.neuroimage.2006.04.210
Vemuri : Groupwise registration and atlas construction of 4th-order tensor fields using the R+ riemannian metric, Medical Image Computing and Computer Assisted Intervention, pp.640-647, 2009. ,
Modha : Concept decompositions for large sparse text data using clustering, Machine Learning, pp.143-175, 2001. ,
Suetens : Spatial transformations of high angular resolution diffusion imaging data in q-space, Medical Image Computing and Computer Assisted Intervention, pp.73-83, 2010. ,
Armspach : A new high order tensor decomposition : application to reorientation, IEEE Internaional Symposium on Biomedical Imaging, pp.258-261, 2011. ,
Interval arithmetic: From principles to implementation, Journal of the ACM, vol.48, issue.5, pp.1038-1068, 1999. ,
DOI : 10.1145/502102.502106
Spatial normalization of the fiber orientation distribution based on high angular resolution diffusion imaging data, Magnetic Resonance in Medicine, vol.56, issue.6, pp.1520-1527, 2009. ,
DOI : 10.1002/mrm.21916
A Simplex Method for Function Minimization, The Computer Journal, vol.7, issue.4, pp.308-313, 1965. ,
DOI : 10.1093/comjnl/7.4.308
Reconstruction of scattered data in fetal diffusion MRI, Medical Image Analysis, vol.16, issue.1, p.2012 ,
URL : https://hal.archives-ouvertes.fr/hal-00680285
Reorientation strategies for high order tensors Quantitative analysis of diffusion tensor orientation : Theoretical framework, IEEE International Symposium on Biomedical Imaging, pp.1185-11881146, 2004. ,
Vemuri : Groupwise registration and atlas construction of 4th-order tensor fields using the R+ riemannian metric, Medical Image Computing and Computer Assisted Intervention, pp.640-647, 2009. ,
Deterministic and Probabilistic Tractography Based on Complex Fibre Orientation Distributions, IEEE Transactions on Medical Imaging, vol.28, issue.2, pp.269-286, 2009. ,
DOI : 10.1109/TMI.2008.2004424
Longitudinal penalized functional regression for cognitive outcomes on neuronal tract measurements, Journal of the Royal Statistical Society: Series C (Applied Statistics), vol.100, issue.3, pp.61453-469, 2012. ,
DOI : 10.1111/j.1467-9876.2011.01031.x
Probabilistic Tractography Using Q-Ball Modeling and Particle Filtering, Medical Image Computing and Computer Assisted Intervention, pp.209-216, 2011. ,
DOI : 10.1016/j.media.2008.05.001
Bias in tensor based morphometry Stat-ROI measures may result in unrealistic power estimates, NeuroImage, vol.57, issue.1, pp.1-4, 2011. ,
DOI : 10.1016/j.neuroimage.2010.11.092
Clatz : DTI registration with exact finite-strain differential, IEEE International Symposium on Biomedical Imaging, pp.700-703, 2008. ,
Co-registration of White Matter Tractographies by Adaptive-Mean-Shift and Gaussian Mixture Modeling, IEEE Transactions on Medical Imaging, vol.29, issue.1, pp.132-145, 2010. ,
DOI : 10.1109/TMI.2009.2029097
Longitudinal change detection in diffusion MRI using multivariate statistical testing on tensors, NeuroImage, vol.60, issue.4, pp.2206-2221, 2012. ,
DOI : 10.1016/j.neuroimage.2012.02.049
Longitudinal Change Detection : Inference on the Diffusion Tensor Along White-Matter Pathways, MICCAI 2011, pp.1-8, 2011. ,
A new high order tensor decomposition: Application to reorientation., 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.258-261, 2011. ,
DOI : 10.1109/ISBI.2011.5872401
Longitudinal change detection in diffusion MRI using multivariate statistical testing on tensors, MICCAI 2010, pp.117-124, 2010. ,
DOI : 10.1016/j.neuroimage.2012.02.049
Comparison of interpolation methods for angular resampling of diffusion weighted images, 2010 2nd International Conference on Image Processing Theory, Tools and Applications, pp.207-211, 2010. ,
DOI : 10.1109/IPTA.2010.5586799
On the integration of spatial neighborhood information for detecting longitudinal changes in MRI sequences, p.2011 ,
Détection de changements en IRM du tenseur de diffusion : application au suivi longitudinal de la sclérose en plaques, RITS 2011, Recherche en Imagerie et Technologies pour la Santé, 2011. ,