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Bibliography

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

Doctoral Dissertations and Habilitation Theses

Articles in International Peer-Reviewed Journals

  • 13S. Bhattacharyya, M. Clerc, M. Hayashibe.

    A study on the effect of electrical stimulation as a user stimuli for motor imagery classification in Brain-Machine Interface, in: European Journal of Translational Myology, June 2016, vol. 26, no 2, pp. 165-168. [ DOI : 10.4081/ejtm.2016.6041 ]

    https://hal-lirmm.ccsd.cnrs.fr/lirmm-01402537
  • 14M. Clerc, J. Leblond, J.-P. Marmorat, C. Papageorgakis.

    Uniqueness result for an inverse conductivity recovery problem with application to EEG, in: Rendiconti dell'Istituto di Matematica dell'Università di Trieste. An International Journal of Mathematics, 2016, vol. 48, Special issue dedicated to Giovanni Alessandrini.

    https://hal.archives-ouvertes.fr/hal-01303640
  • 15R. Deriche.

    Computational Brain Connectivity Mapping: A Core Health and Scientific Challenge, in: Medical Image Analysis, June 2016. [ DOI : 10.1016/j.media.2016.06.003 ]

    https://hal.archives-ouvertes.fr/hal-01335669
  • 16R. H. Fick, D. Wassermann, E. Caruyer, R. Deriche.

    MAPL: Tissue Microstructure Estimation Using Laplacian-Regularized MAP-MRI and its Application to HCP Data, in: NeuroImage, July 2016, vol. 134, pp. 365–385. [ DOI : 10.1016/j.neuroimage.2016.03.046 ]

    https://hal.inria.fr/hal-01291929
  • 17A. Ghosh, R. Deriche.

    A survey of current trends in diffusion MRI for structural brain connectivity, in: Journal of Neural Engineering, February 2016, vol. 13, no 1, 011001 p. [ DOI : 10.1088/1741-2560/13/1/011001 ]

    https://hal.inria.fr/hal-01293828
  • 18A. Pascarella, C. Todaro, M. Clerc, T. Serre, M. Piana.

    Source modeling of ElectroCorticoGraphy (ECoG) data: Stability analysis and spatial filtering, in: Journal of Neuroscience Methods, February 2016. [ DOI : 10.1016/j.jneumeth.2016.02.012 ]

    https://hal.inria.fr/hal-01278377
  • 19D. Wassermann, N. Makris, Y. Rathi, M. Shenton, R. Kikinis, M. Kubicki, C.-F. Westin.

    The white matter query language: a novel approach for describing human white matter anatomy, in: Brain Structure and Function, 2016. [ DOI : 10.1007/s00429-015-1179-4 ]

    https://hal.inria.fr/hal-01247061

Invited Conferences

  • 20T. Papadopoulo.

    Modelling thin tissue compartiments using the immersed FEM (continuous Galerkin), in: Biomag 2016 - 20th International Conference on Biomagnetism, Seoul, South Korea, October 2016.

    https://hal.inria.fr/hal-01412820

International Conferences with Proceedings

  • 21B. Belaoucha, T. Papadopoulo.

    Iterative two-stage approach to estimate sources and their interactions , in: 20th International Conference on Biomagnetism (BIOMAG2016), Seoul, South Korea, October 2016.

    https://hal.inria.fr/hal-01377967
  • 22S. Bhattacharyya, M. Clerc, M. Hayashibe.

    A Study on the Effect of Electrical Stimulation During Motor Imagery Learning in Brain-Computer Interfacing, in: SMC: Systems, Man, and Cybernetics, Budapest, Hungary, October 2016.

    https://hal.archives-ouvertes.fr/hal-01402794
  • 23N. T. H. Gayraud, N. Foy, M. Clerc.

    A Separability Marker Based on High-Dimensional Statistics for Classification Confidence Assessment, in: IEEE International Conference on Systems, Man, and Cybernetics October 9-12, Budapest, Hungary, October 2016.

    https://hal.inria.fr/hal-01407759
  • 24G. Girard, A. Daducci, K. Whittingstall, R. Deriche, D. Wassermann, M. Descoteaux.

    Microstructure ­driven tractography in the human brain , in: Organization for Human Brain Mapping (OHBM), Geneva, Switzerland, Proceedings of: Human Brain Mapping (HBM), June 2016.

    https://hal.archives-ouvertes.fr/hal-01408727
  • 25M. H. Soriani, V. Guy, M. Bruno, T. Papadopoulo, M. Clerc, C. Desnuelle.

    Interface cerveau-ordinateur (BCI) : un moyen de communication alternative dans la SLA, in: Jnlf Nantes 2016 - Journées de Neurologie de langue française 2016, Nantes, France, Revue neurologique, Elsevier, April 2016, vol. 172, no S1.

    https://hal.inria.fr/hal-01413326
  • 26D. Wassermann, D. Mazauric, G. Gallardo-Diez, R. Deriche.

    Extracting the Core Structural Connectivity Network: Guaranteeing Network Connectedness Through a Graph-Theoretical Approach, in: MICCAI 2016, Athens, Greece, September 2016.

    https://hal.inria.fr/hal-01333301

Conferences without Proceedings

  • 27B. Belaoucha, M. Clerc, T. Papadopoulo.

    Cortical Surface Parcellation via dMRI Using Mutual Nearest Neighbor Condition, in: International Symposium on Biomedical Imaging: From Nano to Macro, Prague, Czech Republic, April 2016, pp. 903–906.

    https://hal.archives-ouvertes.fr/hal-01306239
  • 28B. Belaoucha, M. Kachouane, T. Papadopoulo.

    Multivariate Autoregressive Model Constrained by Anatomical Connectivity to Reconstruct Focal Sources, in: The 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Orlando, United States, August 2016.

    https://hal.archives-ouvertes.fr/hal-01357167
  • 29M. Clerc, J. Leblond, J.-P. Marmorat, C. Papageorgakis.

    On some inverse conductivity recovery problem in a sphere: Uniqueness and reconstruction results with applications to EEG, in: Problèmes Inverses, Contrôle et Optimisation de Formes (PICOF), Autrans, France, June 2016.

    https://hal.inria.fr/hal-01410030
  • 30R. H. Fick, M. Daianu, M. Pizzolato, D. Wassermann, R. E. Jacobs, P. M. Thompson, T. Town, R. Deriche.

    Comparison of Biomarkers in Transgenic Alzheimer Rats Using Multi-shell Diffusion MRI, in: MICCAI 2016 Workshop on Computational Diffusion MRI (CDMRI'16), Athènes, Greece, October 2016.

    https://hal.archives-ouvertes.fr/hal-01354981
  • 31R. H. Fick, A. Petiet, M. Santin, A.-C. Philippe, S. Lehericy, R. Deriche, D. Wassermann.

    Multi-Spherical Diffusion MRI: Exploring Diffusion Time Using Signal Sparsity, in: MICCAI 2016 Workshop on Computational Diffusion MRI (CDMRI'16), Athènes, Greece, October 2016.

    https://hal.archives-ouvertes.fr/hal-01354985
  • 32R. H. Fick, M. Pizzolato, D. Wassermann, M. Zucchelli, G. Menegaz, R. Deriche.

    A sensitivity analysis of q-space indices with respect to changes in axonal diameter, dispersion and tissue composition, in: 2016 International Symposium on Biomedical Imaging (ISBI), Prague, Czech Republic, April 2016.

    https://hal.inria.fr/hal-01292013
  • 33G. Gallardo, R. H. Fick, W. Wells Iii, R. Deriche, D. Wassermann.

    Groupwise Structural Parcellation of the Cortex: A Sound Approach Based on Logistic Models, in: MICCAI 2016 Workshop on Computational Diffusion MRI, Athens, Greece, October 2016.

    https://hal.archives-ouvertes.fr/hal-01358436
  • 34G. Gallardo-Diez, R. Deriche, D. Wassermann.

    Efficient Population-Representative Whole-Cortex Parcellation Based on Tractography, in: Organization for Human Brain Mapping (OHBM), Geneva, Switzerland, June 2016.

    https://hal.archives-ouvertes.fr/hal-01408881
  • 35G. Girard, A. Daducci, L. Petit, J.-P. Thiran, K. Whittingstall, R. Deriche, D. Wassermann, M. Descoteaux.

    Reducing Invalid Connections with Microstructure-Driven Tractography, in: ISMRM workshops: Breaking the Barriers of Diffusion MRI, Lisbonne, Portugal, September 2016.

    https://hal.archives-ouvertes.fr/hal-01408737
  • 36C. Lindig-León, N. Gayraud, L. Bougrain, M. Clerc.

    Comparison of Hierarchical and Non-Hierarchical Classification for Motor Imagery Based BCI Systems, in: The Sixth International Brain-Computer Interfaces Meeting, Pacific Groove, United States, May 2016.

    https://hal.inria.fr/hal-01287636
  • 37T. Megherbi, G. Girard, M. Descoteaux, F. Oulebsir Boumghar, R. Deriche.

    Evaluation des méthodes d'extraction des orientations locales des faisceaux de fibres par analyse quantitative de la connectivité, in: Reconnaissance des Formes et l'Intelligence Artificielle (RFIA'16), Clermont-Ferrand, France, June 2016.

    https://hal.archives-ouvertes.fr/hal-01354106
  • 38M. Pizzolato, T. Boutelier, R. H. Fick, R. Deriche.

    Elucidating Dispersion Effects in Perfusion MRI by Means of Dispersion-Compliant Bases, in: International Symposium on Biomedical Imaging (ISBI), Prague, Czech Republic, April 2016. [ DOI : 10.1109/I978-1-4799-2349-6/16 ]

    https://hal.inria.fr/hal-01309243
  • 39M. Pizzolato, R. H. Fick, T. Boutelier, R. Deriche.

    Noise Floor Removal via Phase Correction of Complex Diffusion-Weighted Images: Influence on DTI and q-space Metrics, in: Computational Diffusion MRI, Athens, Greece, October 2016.

    https://hal.inria.fr/hal-01358770

Scientific Books (or Scientific Book chapters)

  • 40M. Clerc, L. Bougrain, F. Lotte.

    Conclusion and Perspectives, in: Brain-Computer Interfaces 2, Wiley-ISTE, July 2016.

    https://hal.inria.fr/hal-01409032
  • 41M. Clerc, L. Bougrain, F. Lotte.

    Conclusion et perspectives, in: Les interfaces cerveau-ordinateur 2, ISTE, July 2016.

    https://hal.inria.fr/hal-01408972
  • 42M. Clerc, L. Bougrain, F. Lotte.

    Introduction, in: Brain-Computer Interfaces 1, M. Clerc, L. Bougrain, F. Lotte (editors), July 2016.

    https://hal.inria.fr/hal-01409001
  • 43M. Clerc, L. Bougrain, F. Lotte.

    Introduction, in: Les interfaces cerveau-ordinateur 1, M. Clerc, L. Bougrain, F. Lotte (editors), Fondements et méthodes, ISTE, July 2016.

    https://hal.inria.fr/hal-01402594
  • 44M. Clerc.

    Electroencephalography Data Preprocessing, in: Brain-Computer Interfaces 1, M. Clerc, L. Bougrain, F. Lotte (editors), Wiley-ISTE, July 2016. [ DOI : 10.1002/9781119144977.ch6 ]

    https://hal.inria.fr/hal-01409009
  • 45M. Clerc.

    Prétraitements de données d'électro-encéphalographie, in: Les interfaces cerveau-ordinateur 1, M. Clerc, L. Bougrain, F. Lotte (editors), July 2016.

    https://hal.inria.fr/hal-01402595
  • 46M. Clerc, E. Daucé, J. Mattout.

    Adaptive Methods in Machine Learning, in: Brain-Computer Interfaces 1, Wiley-ISTE, July 2016.

    https://hal.inria.fr/hal-01409016
  • 47M. Clerc, E. Daucé, J. Mattout.

    Méthodes adaptatives en apprentissage machine, in: Les interfaces cerveau-ordinateur 1, M. Clerc, L. Bougrain, F. Lotte (editors), ISTE, July 2016.

    https://hal.inria.fr/hal-01408906
  • 48N. Foy, T. Papadopoulo, M. Clerc.

    Illustration OpenViBE d'un clavier virtuel P300, in: Les interfaces cerveau-ordinateur 2, M. Clerc, L. Bougrain, F. Lotte (editors), ISTE, July 2016.

    https://hal.inria.fr/hal-01408947
  • 49N. Foy, T. Papadopoulo, M. Clerc.

    OpenViBE Illustration of a P300 Virtual Keyboard, in: Brain-Computer Interfaces 2, M. Clerc, L. Bougrain, F. Lotte (editors), Wiley-ISTE, July 2016. [ DOI : 10.1002/9781119332428.ch13 ]

    https://hal.inria.fr/hal-01409029
  • 50L. Perronnet, A. Lécuyer, F. Lotte, M. Clerc, C. Barillot.

    Brain training with neurofeedback, in: Brain-Computer Interfaces 1, Wiley-ISTE, July 2016.

    https://hal.inria.fr/hal-01413424
  • 51L. Perronnet, A. Lécuyer, F. Lotte, M. Clerc, C. Barillot.

    Entraîner son cerveau avec le neurofeedback, in: Les interfaces cerveau-ordinateur 1, M. Clerc, L. Bougrain, F. Lotte (editors), July 2016.

    https://hal.inria.fr/hal-01413408

Books or Proceedings Editing

  • 52M. Clerc, L. Bougrain, F. Lotte (editors)

    Brain-Computer Interfaces 1: Foundations and Methods, Wiley-ISTE, July 2016.

    https://hal.inria.fr/hal-01408991
  • 53M. Clerc, L. Bougrain, F. Lotte (editors)

    Brain-Computer Interfaces 2: Technology and Applications, Wiley-ISTE, July 2016.

    https://hal.inria.fr/hal-01408998
  • 54M. Clerc, L. Bougrain, F. Lotte (editors)

    Les interfaces Cerveau-Ordinateur 1 : Fondements et méthodes, ISTE, July 2016.

    https://hal.inria.fr/hal-01402539
  • 55M. Clerc, L. Bougrain, F. Lotte (editors)

    Les interfaces cerveau-ordinateur 2 : Technologie et applications, ISTE, July 2016.

    https://hal.inria.fr/hal-01402544
  • 56M. Pizzolato, T. Boutelier, R. Deriche (editors)

    Effect of Phase Correction on DTI and q-space Metrics, International Society for Magnetic Resonance in Medicine, September 2016.

    https://hal.inria.fr/hal-01408421
  • 57M. Pizzolato, R. H. Fick, T. Boutelier, R. Deriche (editors)

    Unveiling the Dispersion Kernel in DSC-MRI by Means of Dispersion-Compliant Bases and Control Point Interpolation Techniques, Proc. Int. Soc. Mag. Reson. Med. 24 (2016), March 2016.

    https://hal.inria.fr/hal-01408170

Other Publications

  • 58K. Dang, P. Stahl, C. Vandersteen, N. Guevara, D. Gnansia, M. Clerc.

    Evaluation of the current distribution of the hybrid common ground stimulation in cochlear implants, June 2016, 9th International Symposium on Objective Measures in Auditory Implants (OMAI), Poster.

    https://hal.inria.fr/hal-01377653
  • 59R. H. Fick, A. Petiet, M. Santin, A.-C. Philippe, S. Lehericy, R. Deriche, D. Wassermann.

    Multi-Spherical MRI: Breaking the Boundaries of Diffusion Time, September 2016, ISMRM Workshop on: Breaking the Barriers of Diffusion MRI, Poster.

    https://hal.archives-ouvertes.fr/hal-01360440
  • 60M. Pizzolato, R. H. Fick, T. Boutelier, R. Deriche.

    Improved Vascular Transport Function Characterization in DSC-MRI via Deconvolution with Dispersion-Compliant Bases, May 2016, ISMRM 2016, Poster.

    https://hal.inria.fr/hal-01358775
  • 61D. Wassermann, A. Petiet, M. Santin, R. H. Fick, A.-C. Philippe, S. Lehericy, R. Deriche.

    Quantifying White Matter Microstructure with aUnified Spatio-Temporal Diffusion Weighted MRIContinuous Representation, 2016, International Symposium of Magnetic Resonance in Medicine, Poster.

    https://hal.inria.fr/hal-01406348
References in notes
  • 62H. Johansen-Berg, T. E. Behrens (editors)

    Diffusion MRI : From Quantitative Measurement to In vivo Neuroanatomy, Elevier - Academic Press, 2009.
  • 63D. K. Jones (editor)

    Diffusion MRI: Theory, Methods, and Applications, Oxford University Press, 2011.
  • 64Y. 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.
  • 65Y. 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
  • 66H.-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.

    http://dx.doi.org/10.1007/978-3-642-23629-7_20
  • 67H. Assemlal, D. Tschumperlé, L. Brun.

    Efficient and robust computation of PDF features from diffusion MR signal, in: Medical Image Analysis, 2009, vol. 13, no 5, pp. 715–729.
  • 68A. 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
  • 69P. J. Basser, J. Mattiello, D. Le Bihan.

    Estimation of the effective self-diffusion tensor from the NMR spin echo, in: Journal of Magnetic Resonance, 1994, vol. B, no 103, pp. 247–254.
  • 70P. J. Basser, J. Mattiello, D. Le Bihan.

    MR Diffusion Tensor Spectroscopy and imaging, in: Biophysical Journal, 1994, vol. 66, no 1, pp. 259–267.
  • 71B. Belaoucha, A.-C. Philippe, M. Clerc, T. Papadopoulo.

    Diffusion Magnetic Resonance information as a regularization term for MEG/EEG inverse problem, in: BIOMAG, Halifax, Canada, August 2014.
  • 72P. T. Callaghan.

    Principles of nuclear magnetic resonance microscopy, Oxford University Press, Oxford, 1991.
  • 73E. Caruyer.

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

    http://hal.inria.fr/tel-00750144
  • 74J. 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
  • 75R. 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
  • 76M. 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
  • 77M. 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
  • 78M. 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 ]

    http://www.sciencedirect.com/science/article/B6W6Y-50HYGF0-1/2/647c6da427c692f0968d6647ecb952f7
  • 79M. 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
  • 80Q. Dong, R. Welsh, T. Chenevert, R. Carlos, P. Maly-Sundgren, D. Gomez-Hassan, S. Mukherji.

    Clinical Applications of Diffusion Tensor Imaging, in: Journal of Magnetic Resonance Imaging, 2004, vol. 19, pp. 6–18.
  • 81A. 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
  • 82A. 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/
  • 83A. 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
  • 84A. 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
  • 85A. 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
  • 86E. Hubert.

    Rational Invariants of a Group Action, in: Journees Nationales de Calcul Formel, CEDRAM - Center for Diffusion of Academic Mathematical Journals, P. Boito, G. Chèze, C. Pernet, M. S. E. Din (editors), Les cours du CIRM, 2013, vol. 3, 10p p.
  • 87E. Hubert, I. A. Kogan.

    Rational invariants of a group action. Construction and rewriting, in: Journal of Symbolic Computation, 2007, vol. 42, no 1-2, pp. 203–217.
  • 88E. Hubert, I. A. Kogan.

    Smooth and algebraic invariants of a group action. Local and global constructions, in: Foundations of Computational Mathematics, 2007, vol. 7, no 4.
  • 89J. 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
  • 90D. Le Bihan, E. Breton.

    Imagerie de Diffusion in vivo par Résonnance Magnétique Nucléaire, in: CR Académie des Sciences, 1985, no 301, pp. 1109-1112.
  • 91D. 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
  • 92C. 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
  • 93C. 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
  • 94K. Merboldt, W. Hanicke, J. Frahm.

    Self-diffusion NMR Imaging Using Stimulated Echoes, in: J. Magn. Reson., 1985, vol. 64, pp. 479–486.
  • 95S. Merlet.

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

    https://tel.archives-ouvertes.fr/tel-00908369/
  • 96E. Ozarslan, C. Koay, T. Shepherd, S. Blackband, P. Basser.

    Simple harmonic oscillator based reconstruction and estimation for three-dimensional q-space MRI, in: ISMRM 17th Annual Meeting and Exhibition, Honolulu,, 2009, 1396. p.

    http://stbb.nichd.nih.gov/abstracts.html
  • 97E. Ozarslan, C. Koay, T. Shepherd, M. Komlosh, M. Irfanoglu, C. Pierpaoli, P. J. Basser.

    Mean apparent propagator (MAP) MRI: a novel diffusion imaging method for mapping tissue microstructure., in: Neuroimage, September 2013, vol. 78, pp. 16–32.

    stbb.nichd.nih.gov/pdf/MAP-MRI.pdf
  • 98E. 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. [ DOI : 10.1016/j.neuroimage.2011.09.081 ]

    http://www.ucl.ac.uk/cabi/PDF/2012_Panagiotaki_et_al._NeuroImage.pdf
  • 99T. 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
  • 100T. Schultz, A. Fuster, A. Ghosh, R. Deriche, L. Florack, L.-H. Lim.

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