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Bibliography

Major publications by the team in recent years Publications of the year

Articles in International Peer-Reviewed Journals

  • 8T. Brochier, R. Trachel, M. Clerc.

    Brain-computer interaction for online enhancement of visuospatial attention performance, in: Journal of Neural Engineering, 2018, vol. 15, no 4. [ DOI : 10.1088/1741-2552/aabf16 ]

    https://hal.archives-ouvertes.fr/hal-01794034
  • 9D. Cherifi, M. Boudjada, A. Morsli, G. Girard, R. Deriche.

    Combining Improved Euler and Runge-Kutta 4th order for Tractography in Diffusion-Weighted MRI, in: Biomedical Signal Processing and Control, March 2018, vol. 41, pp. 90 - 99. [ DOI : 10.1016/j.bspc.2017.11.008 ]

    https://hal.archives-ouvertes.fr/hal-01928276
  • 10M. Dali, O. Rossel, D. Andreu, L. Laporte, A. Hernández, J. Laforet, E. Marijon, A. A. Hagège, M. Clerc, C. Henry, D. Guiraud.

    Model based optimal multipolar stimulation without a priori knowledge of nerve structure: application to vagus nerve stimulation, in: Journal of Neural Engineering, May 2018, vol. 15, no 4, 046018 p. [ DOI : 10.1088/1741-2552/aabeb9 ]

    https://hal-lirmm.ccsd.cnrs.fr/lirmm-01770039
  • 11R. H. Fick, A. Petiet, M. Santin, A.-C. Philippe, S. Lehéricy, R. Deriche, D. Wassermann.

    Non-Parametric GraphNet-Regularized Representation of dMRI in Space and Time, in: Medical Image Analysis, 2018, vol. 43, pp. 37–53. [ DOI : 10.1016/j.media.2017.09.002 ]

    https://hal.inria.fr/hal-01578296
  • 12P. Filipiak, R. H. Fick, A. Petiet, M. Santin, A.-C. Philippe, S. Lehéricy, P. Ciuciu, R. Deriche, D. Wassermann.

    Reducing the number of samples in spatiotemporal dMRI acquisition design, in: Magnetic Resonance in Medicine, November 2018. [ DOI : 10.1002/mrm.27601 ]

    https://hal.archives-ouvertes.fr/hal-01928734
  • 13Y. Hong, L. J. O'Donnell, P. Savadjiev, F. Zhang, D. Wassermann, O. Pasternak, H. J. Johnson, J. Paulsen, J.-P. Vonsattel, N. Makris, C.-F. Westin, Y. Rathi.

    Genetic load determines atrophy in hand cortico-striatal pathways in presymptomatic Huntington’s disease, in: Human Brain Mapping, 2018. [ DOI : 10.1002/hbm.24217 ]

    https://hal.inria.fr/hal-01787886
  • 14F. Lotte, L. Bougrain, A. Cichocki, M. Clerc, M. Congedo, A. Rakotomamonjy, F. Yger.

    A Review of Classification Algorithms for EEG-based Brain-Computer Interfaces: A 10-year Update, in: Journal of Neural Engineering, April 2018, 55 p.

    https://hal.inria.fr/hal-01846433
  • 15T. Megherbi, G. Girard, A. Ghosh, F. Oulebsir-Boumghar, R. Deriche.

    Fiber orientation distribution function from non-negative sparse recovery with quantitative analysis of local fiber orientations and tractography using DW-MRI datasets, in: Magnetic Resonance Imaging, October 2018. [ DOI : 10.1016/j.mri.2018.10.003 ]

    https://hal.archives-ouvertes.fr/hal-01912555
  • 16S. Merino-Caviedes, L. Cordero-Grande, M. T. Perez, P. Casaseca-de-la-Higuera, M. Martín-Fernández, R. Deriche, C. Alberola-Lopez.

    A Second Order Multi-Stencil Fast Marching Method with a Non-Constant Local Cost Model, in: IEEE Transactions on Image Processing, 2018, 1 p. [ DOI : 10.1109/TIP.2018.2880507 ]

    https://hal.archives-ouvertes.fr/hal-01921997
  • 17V. Sydnor, A. M. Rivas-Grajales, A. Lyall, F. Zhang, S. Bouix, S. Karmacharya, M. Shenton, C.-F. Westin, N. Makris, D. Wassermann, L. J. O'Donnell, M. Kubicki.

    A comparison of three fiber tract delineation methods and their impact on white matter analysis, in: NeuroImage, May 2018, vol. 178, pp. 318-331. [ DOI : 10.1016/j.neuroimage.2018.05.044 ]

    https://hal.inria.fr/hal-01807178

Invited Conferences

  • 18L. Caroux, E. Campo, N. Vigouroux, E. Bourreau, M. Clerc, P. Gorce, C. Graff, M. Huchard, D. Istrate, J. Jacquier-Bret, N. Lompré, N. Pinede, L. R. Duarte, M. Sacher, A. Serna, A. Serpa, A. Van Den Bossche, F. Vella.

    MAN : Mise en Place d'une Méthode d’Évaluation Croisée de l'Accès aux Ressources Numériques, in: HANDICAP, Paris, France, Actes du Congrès Handicap 2018 - 10ème édition, June 2018, pp. 211-212.

    https://hal.archives-ouvertes.fr/hal-01815554
  • 19M. Clerc.

    Conductivity models for functional neuroimaging, in: SIAM Conference on Imaging Science, Bologna, Italy, June 2018.

    https://hal.inria.fr/hal-01888187
  • 20T. Papadopoulo.

    Inverse source problems in electro- and magneto- encephalography, in: Inverse problems: modeling and simulation, Paradise Bay, Malta, May 2018.

    https://hal.inria.fr/hal-01963644

International Conferences with Proceedings

  • 21A. Alimi, R. H. Fick, D. Wassermann, R. Deriche.

    Dmipy, a Diffusion Microstructure Imaging toolbox in Python to improve research reproducibility, in: MICCAI 2018 - Workshop on Computational Diffusion MRI, Granada, Spain, September 2018.

    https://hal.inria.fr/hal-01873353
  • 22A. Alimi, Y. Usson, P.-S. Jouk, G. Michalowicz, R. Deriche.

    An Analytical Fiber ODF Reconstruction in 3D Polarized Light Imaging, in: ISBI 2018 - IEEE International Symposium on Biomedical Imaging, Washington, D.C., United States, April 2018, pp. 1-4.

    https://hal.inria.fr/hal-01688789
  • 23I. Costantini, P. Filipiak, K. Maksymenko, S. Deslauriers-Gauthier, R. Deriche.

    fMRI Deconvolution via Temporal Regularization using a LASSO model and the LARS algorithm, in: EMBC'18 - 40th International Engineering in Medicine and Biology Conference, Honolulu, United States, July 2018.

    https://hal.inria.fr/hal-01855467
  • 24S. Deslauriers-Gauthier, D. Parker, F. Rheault, R. Deriche, S. Brem, M. Descoteaux, R. Verma.

    Edema-informed anatomically constrained particle filter tractography, in: Medical Image Computing and Computer Assisted Intervention – MICCAI 2018, Granada, Spain, September 2018.

    https://hal.inria.fr/hal-01893110
  • 25M. Frigo, I. Costantini, R. Deriche, S. Deslauriers-Gauthier.

    Resolving the crossing/kissing fiber ambiguity using Functionally Informed COMMIT, in: Computational Diffusion MRI 2018, Granada, Spain, September 2018.

    https://hal.inria.fr/hal-01864939
  • 26G. Gallardo, N. Gayraud, R. Deriche, M. Clerc, S. Deslauriers-Gauthier, D. Wassermann.

    Solving the Cross-Subject Parcel Matching Problem using Optimal Transport, in: International Conference on Medical Image Computing and Computer-Assisted Intervention 2018, Granada, Spain, September 2018.

    https://hal.archives-ouvertes.fr/hal-01935684
  • 27K. Maksymenko, M. Clerc, T. Papadopoulo.

    Data-driven cortical clustering to provide a family of plausible solutions to M/EEG inverse problem, in: iTWIST, Marseille, France, November 2018, https://arxiv.org/abs/1812.04110.

    https://hal.inria.fr/hal-01946876
  • 28F. Turi, N. T. H. Gayraud, M. Clerc.

    Zero-calibration cVEP BCI using word prediction: a proof of concept, in: BCI 2018 - 7th International BCI Meeting, Pacific Grove, California, United States, May 2018, https://arxiv.org/abs/1810.03428.

    https://hal.inria.fr/hal-01878015
  • 29M. Zucchelli, S. Deslauriers-Gauthier, R. Deriche.

    A Closed-Form Solution of Rotation Invariant Spherical Harmonic Features in Diffusion MRI, in: MICCAI - Computational Diffusion MRI Workshop 2018, Granada, Spain, September 2018.

    https://hal.inria.fr/hal-01912148

Conferences without Proceedings

  • 30R. H. Fick, D. Wassermann, R. Deriche.

    Mipy: An Open-Source Framework to improve reproducibility in Brain Microstructure Imaging, in: OHBM 2018 - Human Brain Mapping, Singapore, Singapore, June 2018, pp. 1-4.

    https://hal.archives-ouvertes.fr/hal-01722146
  • 31M. Frigo, G. Gallardo, I. Costantini, A. Daducci, D. Wassermann, R. Deriche, S. Deslauriers-Gauthier.

    Reducing false positive connection in tractograms using joint structure-function filtering, in: OHBM 2018 - Organization for Human Brain Mapping, Singapore, Singapore, June 2018, pp. 1-3.

    https://hal.inria.fr/hal-01737434
  • 32N. T. H. Gayraud, G. Gallardo, M. Clerc, D. Wassermann.

    Solving the Cross-Subject Parcel Matching Problem: Comparing Four Methods Using Extrinsic Connectivity, in: OHBM 2018, Singapore, Singapore, June 2018.

    https://hal.archives-ouvertes.fr/hal-01737366
  • 33S. Rimbert, N. Gayraud, M. Clerc, S. Fleck, L. Bougrain.

    Can the MIQ-RS questionnaire be used to estimate the performance of a MI-based BCI?, in: 2018 Seventh International BCI Meeting, Pacific Grove, United States, May 2018.

    https://hal.archives-ouvertes.fr/hal-01889864
  • 34M. Zucchelli, M. Descoteaux, G. Menegaz.

    Investigating Diffusion-MRI based neurite density estimation model dependency: an in-vivo study on the HCP dataset, in: ISMRM 2018 - International Society for Magnetic Resonance in Medicine, Paris, France, June 2018.

    https://hal.inria.fr/hal-01831823

Other Publications

  • 35A. Alimi, A. Petiet, M. Santin, A.-C. Philippe, S. Lehéricy, R. Deriche, D. Wassermann.

    Towards the assessment of myelination using time-dependent diffusion MRI indices, June 2018, pp. 1-4, ISMRM 2018 - International Society for Magnetic Resonance in Medicine, Poster.

    https://hal.inria.fr/hal-01723846
  • 36F. Almairac, P. Filipiak, L. Slabu, M. Clerc, T. Papadopoulo, D. Fontaine, L. Mondot, S. Chanelet, D. Wassermann, R. Deriche.

    Bridging Brain Structure and Function by Correlating Structural Connectivity and Cortico-Cortical Transmission, June 2018, 2nd C@UCA meeting, Poster.

    https://hal.inria.fr/hal-01852956
  • 37I. Costantini, P. Filipiak, K. Maksymenko, S. Deslauriers-Gauthier, R. Deriche.

    L1-Norm Regularized Deconvolution of Functional MRI BOLD Signal, June 2018, C@UCA, Poster.

    https://hal.inria.fr/hal-01855505
  • 38P. Filipiak, R. H. Fick, A. Petiet, M. Santin, A.-C. Philippe, S. Lehéricy, R. Deriche, D. Wassermann.

    Spatio-Temporal dMRI Acquisition Design: Reducing the Number of Samples, June 2018, ISMRM 2018, Poster.

    https://hal.inria.fr/hal-01719646
  • 39P. Görlach, E. Hubert, T. Papadopoulo.

    Rational invariants of even ternary forms under the orthogonal group, July 2018, working paper or preprint.

    https://hal.inria.fr/hal-01570853
  • 40K. Maksymenko, M. Clerc, T. Papadopoulo.

    Data-driven cortical clustering to provide a family of plausible solutions to the M/EEG inverse problem, August 2018, BIOMAG 2018, Poster.

    https://hal.archives-ouvertes.fr/hal-01874281
  • 41K. Maksymenko, M. Clerc, T. Papadopoulo.

    Fast Approximation of EEG Forward Problem and Application to Tissue Conductivity Estimation, October 2018, https://arxiv.org/abs/1810.04410 - working paper or preprint.

    https://hal.inria.fr/hal-01890242
  • 42D. Wassermann, D. V. Nguyen, G. Gallardo, J.-R. Li, W. Cai, V. Menon.

    Sensing Von Economo Neurons in the Insula with Multi-shell Diffusion MRI, 2018, International Society for Magnetic Resonance in Medicine, Poster.

    https://hal.inria.fr/hal-01807704
References in notes
  • 43H. Johansen-Berg, T. E. J. Behrens (editors)

    Diffusion MRI : From Quantitative Measurement to In vivo Neuroanatomy, Elevier - Academic Press, 2009.
  • 44D. K. Jones (editor)

    Diffusion MRI: Theory, Methods, and Applications, Oxford University Press, 2011.
  • 45Y. Assaf, P. Basser.

    Composite hindered and restricted model of diffusion (CHARMED) MR imaging of the human brain, in: Neuroimage, August 2005, vol. 27, no 1, pp. 48-58.
  • 46Y. Assaf, T. Blumenfeld-Katzir, Y. Yovel, P. J. Basser.

    AxCaliber: a method for measuring axon diameter distribution from diffusion MRI, in: Magnetic Resonance in Medicine, 2008, vol. 59, no 6, pp. 1347–54.

    http://www.ncbi.nlm.nih.gov/pubmed/18506799
  • 47H.-E. Assemlal, J. Campbell, B. Pike, K. Siddiqi.

    Apparent Intravoxel Fibre Population Dispersion (FPD) Using Spherical Harmonics, in: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2011, G. Fichtinger, A. Martel, T. Peters (editors), Lecture Notes in Computer Science, Springer Berlin / Heidelberg, 2011, vol. 6892, pp. 157-165.

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    Efficient and robust computation of PDF features from diffusion MR signal, in: Medical Image Analysis, 2009, vol. 13, no 5, pp. 715–729.
  • 49A. Barmpoutis, M. S. Hwang, D. Howland, J. R. Forder, B. C. Vemuri.

    Regularized Positive-Definite Fourth-Order Tensor Field Estimation from DW-MRI, in: NeuroImage, March 2009, vol. 45, no 1, pp. S153-162.. [ DOI : 10.1016/j.neuroimage.2008.10.056 ]

    http://www.sciencedirect.com/science/journal/10538119
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  • 51P. J. Basser, J. Mattiello, D. Le Bihan.

    MR Diffusion Tensor Spectroscopy and imaging, in: Biophysical Journal, 1994, vol. 66, no 1, pp. 259–267.
  • 52B. Belaoucha, J.-M. Lina, M. Clerc, A.-C. Philippe, C. Grova, T. Papadopoulo.

    Using diffusion MRI information in the Maximum Entropy on Mean framework to solve MEG/EEG inverse problem, in: BIOMAG, Halifax, Canada, August 2014.
  • 53P. T. Callaghan.

    Principles of nuclear magnetic resonance microscopy, Oxford University Press, Oxford, 1991.
  • 54E. Caruyer.

    Q-Space diffusion MRI: Acquisition and signal processing, University of Nice Sophia Antipolis, July 2012.

    http://hal.inria.fr/tel-00750144
  • 55E. Caruyer, R. Verma.

    On facilitating the use of {HARDI} in population studies by creating rotation-invariant markers, in: Medical Image Analysis, 2015, vol. 20, no 1, pp. 87 - 96. [ DOI : 10.1016/j.media.2014.10.009 ]

    http://www.sciencedirect.com/science/article/pii/S1361841514001558
  • 56J. Cheng.

    Estimation and Processing of Ensemble Average Propagator and Its Features in Diffusion MRI, University of Nice Sophia Antipolis, May 2012.

    http://hal.inria.fr/tel-00759048
  • 57R. Deriche, J. Calder, M. Descoteaux.

    Optimal Real-Time Q-Ball Imaging Using Regularized Kalman Filtering with Incremental Orientation Sets, in: Medical Image Analysis, August 2009, vol. 13, no 4, pp. 564–579.

    http://dx.doi.org/10.1016/j.media.2009.05.008
  • 58M. Descoteaux, E. Angelino, S. Fitzgibbons, R. Deriche.

    Apparent Diffusion Coefficients from High Angular Resolution Diffusion Imaging: Estimation and Applications, in: Magnetic Resonance in Medicine, 2006, vol. 56, pp. 395–410.

    ftp://ftp-sop.inria.fr/odyssee/Publications/2006/descoteaux-angelino-etal:06c.pdf
  • 59M. Descoteaux, R. Deriche.

    High Angular Resolution Diffusion MRI Segmentation Using Region-Based Statistical Surface Evolution, in: Journal of Mathematical Imaging and Vision, February 2009, vol. 33, no 2, pp. 239-252.

    ftp://ftp-sop.inria.fr/odyssee/Publications/2009/descoteaux-deriche:09.pdf
  • 60M. Descoteaux, R. Deriche, D. Le Bihan, J.-F. Mangin, C. Poupon.

    Multiple q-shell diffusion propagator imaging, in: Medical Image Analysis, 2011, vol. 15, no 4, pp. 603–621. [ DOI : DOI: 10.1016/j.media.2010.07.001 ]

    https://www.sciencedirect.com/science/article/pii/S1361841510000939
  • 61M. Descoteaux.

    High Angular Resolution Diffusion MRI: From Local Estimation to Segmentation and Tractography, University of Nice Sophia Antipolis, February 2008.

    ftp://ftp-sop.inria.fr/odyssee/Publications/PhDs/descoteaux_thesis.pdf
  • 62Q. Dong, R. C. Welsh, T. L. Chenevert, R. C. Carlos, P. Maly-Sundgren, D. M. Gomez-Hassan, S. K. Mukherji.

    Clinical Applications of Diffusion Tensor Imaging, in: Journal of Magnetic Resonance Imaging, 2004, vol. 19, pp. 6–18.
  • 63P. Durand, V. Auboiroux, V. Rohu, L. Langar, F. Berger, E. Labyt.

    Glial tumor localization and characterization using DTI augmented MEG modelling, in: Proceedings of Biomag, Halifax, Canada, Biomag, 2014.
  • 64A. Ghosh, R. Deriche.

    From Second to Higher Order Tensors in Diffusion-MRI, in: Tensors in Image Processing and Computer Vision, S. Aja-Fernández, R. de Luis García, D. Tao, X. Li (editors), Advances in Pattern Recognition, Springer London, May 2009, chap. 9, pp. 315-. [ DOI : 10.1007/978-1-84882-299-3 ]

    http://www.springer.com/computer/computer+imaging/book/978-1-84882-298-6
  • 65A. Ghosh, R. Deriche.

    From Diffusion MRI to Brain Connectomics, in: Modeling in Computational Biology and Medicine: A Multidisciplinary Endeavor, F. Cazals, P. Kornprobst (editors), Springer, 2013, chap. 6, pp. 193–231.

    http://hal.inria.fr/hal-00667912/
  • 66A. Ghosh.

    High Order Models in Diffusion MRI and Applications, University of Nice Sophia Antipolis, April 2011.

    ftp://ftp-sop.inria.fr/athena/Publications/PhDs/ghosh:11.pdf
  • 67A. Ghosh, T. Milne, R. Deriche.

    Constrained Diffusion Kurtosis Imaging Using Ternary Quartics & MLE, in: Magnetic Resonance in Medicine, July 2013, Article first published online: 2 JUL 2013 - Volume 71, Issue 4, April 2014, Pages: 1581–1591. [ DOI : 10.1002/mrm.24781 ]

    http://hal.inria.fr/hal-00789755
  • 68A. Ghosh, T. Papadopoulo, R. Deriche.

    Biomarkers for HARDI: 2nd & 4th Order Tensor Invariants, in: IEEE International Symposium on Biomedical Imaging (ISBI), Barcelona, May 2012.

    http://hal.inria.fr/hal-00667905/
  • 69A. Ghosh, T. Papadopoulo, R. Deriche.

    Generalized Invariants of a 4th order tensor: Building blocks for new biomarkers in dMRI, in: Computational Diffusion MRI Workshop (CDMRI), MICCAI, E. Panagiotaki, L. O'Donnell, T. Schultz, G. H. Zhang (editors), 2012, pp. 165–173.

    http://hal.inria.fr/hal-00789763
  • 70J. Kybic, M. Clerc, T. Abboud, O. Faugeras, R. Keriven, T. Papadopoulo.

    A Common Formalism for the Integral Formulations of the Forward EEG Problem, in: IEEE Transactions on Medical Imaging, January 2005, vol. 24, pp. 12–28.

    ftp://ftp-sop.inria.fr/odyssee/Publications/2005/kybic-clerc-etal:05.pdf
  • 71D. Le Bihan, E. Breton.

    Imagerie de Diffusion in vivo par Résonnance Magnétique Nucléaire, in: CR Académie des Sciences, 1985, no 301, pp. 1109-1112.
  • 72D. Le Bihan, J.-F. Mangin, C. Poupon, C. Clark, S. Pappata, N. Molko, H. Chabriat.

    Diffusion tensor imaging: concepts and applications, in: J Magn Reson Imaging., 2001, vol. 13, no 4, pp. 534-46.

    http://www.ncbi.nlm.nih.gov/pubmed/11276097
  • 73C. Lenglet, J. S. W. Campbell, M. Descoteaux, G. Haro, P. Savadjiev, D. Wassermann, A. Anwander, R. Deriche, G. B. Pike, G. Sapiro, K. Siddiqi, P. Thompson.

    Mathematical Methods for Diffusion MRI Processing, in: NeuroImage, March 2009, vol. 45, no 1, pp. S111–S122.

    ftp://ftp-sop.inria.fr/odyssee/Publications/2009/lenglet-campbell-etal:09.pdf
  • 74C. Lenglet, M. Rousson, R. Deriche.

    DTI Segmentation by Statistical Surface Evolution, in: IEEE Transactions on Medical Imaging,, June 2006, vol. 25, no 06, pp. 685–700.

    ftp://ftp-sop.inria.fr/odyssee/Publications/2006/lenglet-rousson-etal:06c.pdf
  • 75F. Lotte, M. Congedo, A. Lécuyer, F. Lamarche, B. Arnaldi.

    A Review of Classification Algorithms for EEG-based Brain-Computer Interfaces, in: Journal of Neural Engineering, 2007, vol. 4, pp. 1–13.
  • 76L. Meng, J. Xiang, D. Rose, R. Kotecha, J. Vannest, A. Byars, T. Degrauw.

    White Matter Abnormalities in Children with Temporal Lobe Epilepsy: A DTI and MEG Study, in: 17th International Conference on Biomagnetism Advances in Biomagnetism–Biomag2010, Springer, 2010, pp. 397–400.
  • 77K. Merboldt, W. Hanicke, J. Frahm.

    Self-diffusion NMR Imaging Using Stimulated Echoes, in: J. Magn. Reson., 1985, vol. 64, pp. 479–486.
  • 78S. Merlet.

    Diffusion MRI & Compressive Sensing, Nice Sophia Antipolis University, September 2013.

    https://tel.archives-ouvertes.fr/tel-00908369/
  • 79I. Mohamed, H. Otsubo, M. Shroff, E. Donner, J. Drake, O. Snead III.

    Magnetoencephalography and diffusion tensor imaging in gelastic seizures secondary to a cingulate gyrus lesion, in: Clinical neurology and neurosurgery, 2007, vol. 109, no 2, pp. 182–187.
  • 80E. Panagiotaki, T. Schneider, B. Siow, M. G. Hall, M. F. Lythgoe, D. C. Alexander.

    Compartment models of the diffusion MR signal in brain white matter: A taxonomy and comparison, in: NeuroImage, 2012, vol. 59, pp. 2241–2254.

    https://doi.org/10.1016/j.neuroimage.2011.09.081
  • 81T. Papadopoulo, A. Ghosh, R. Deriche.

    Complete set of Invariants of a 4th order tensor: the 12 tasks of HARDI from Ternary Quartics, in: Medical Image Computing and Computer-Assisted Intervention - MICCAI, Boston, USA, September 2014, vol. 17, pp. 233–240. [ DOI : 10.1007/978-3-319-10443-0_30 ]

    https://hal.archives-ouvertes.fr/hal-01092492
  • 82A.-C. Philippe, M. Clerc, T. Papadopoulo, R. Deriche.

    A nested cortex parcellation combining analysis of MEG forward problem and diffusion MRI tractography, in: IEEE International Symposium on Biomedical Imaging (ISBI), Barcelona, IEEE, May 2012, pp. 518–521.
  • 83A.-C. Philippe, T. Papadopoulo, C. Bénar, J.-M. Badier, M. Clerc, R. Deriche.

    Propagation of epileptic spikes revealed by diffusion-based constrained MEG source reconstruction, in: 19th International Conference on Biomagnetism (BIOMAG 2014), Halifax, Canada, August 2014.

    http://www.biomag2014.org
  • 84T. Schultz, A. Fuster, A. Ghosh, R. Deriche, L. Florack, L.-H. Lim.

    Higher-Order Tensors in Diffusion Imaging, in: Visualization and Processing of Tensors and Higher Order Descriptors for Multi-Valued Data, C.-F. Westin, B. Burgeth (editors), Springer, 2013, Dagstuhl Reports.

    http://hal.inria.fr/hal-00848526
  • 85S. Sockeel, D. Schwartz, H. Benali.

    Detection of large-scale networks in EEG and comparison with fMRI, in: Proceedings of Biomag, Paris, France, BIOMAG, August 2012.
  • 86S. N. Sotiropoulos, T. E. Behrens, S. Jbabdia.

    Ball and Rackets: Inferring Fibre Fanning from Diffusion-weighted MRI, in: NeuroImage, January 2012, vol. 60, pp. 1412–1425.

    http://dx.doi.org/10.1016/j.neuroimage.2012.01.056
  • 87E. O. Stejskal, J. E. Tanner.

    Spin diffusion measurements: spin echoes in the presence of a time-dependent field gradient, in: Journal of Chemical Physics, 1965, vol. 42, pp. 288–292.
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    The spatial mapping of translational diffusion coefficients by the NMR imaging technique, in: Phys. Med. Biol., 1985, vol. 30, pp. 345-349.

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  • 89D. Tuch.

    Q-Ball Imaging, in: Magnetic Resonance in Medicine, 2004, vol. 52, no 6, pp. 1358–1372.
  • 90S. Vallaghé, M. Clerc, J.-M. Badier.

    In vivo conductivity estimation using somatosensory evoked potentials and cortical constraint on the source, in: Proceedings of ISBI, April 2007, pp. 1036–1039.

    http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4193466
  • 91V. J. Wedeen, P. Hagmann, W. Tseng, T. G. Reese, R. M. Weisskoff.

    Mapping complex tissue architecture with diffusion spectrum magnetic resonance imaging, in: Magnetic Resonance in Medicine, 2005, vol. 54, no 6, pp. 1377–1386.
  • 92H. Zhang, T. Schneider, C. A. Wheeler-Kingshott, D. C. Alexander.

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