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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

  • 9S. Bhattacharyya, M. Clerc, M. Hayashibe.

    Augmenting Motor Imagery Learning for Brain–Computer Interfacing Using Electrical Stimulation as Feedback, in: IEEE Transactions on Medical Robotics and Bionics, November 2019, vol. 1, no 4, pp. 247-255. [ DOI : 10.1109/TMRB.2019.2949854 ]

    https://hal.inria.fr/hal-02401304
  • 10L. Chen, D. Wassermann, D. Abrams, J. Kochalka, G. Gallardo-Diez, V. Menon.

    The visual word form area (VWFA) is part of both language and attention circuitry, in: Nature Communications, December 2019, vol. 10, no 1, Lang Chen, Demian Wassermann, and Daniel Abrams contributed equally. [ DOI : 10.1038/s41467-019-13634-z ]

    https://hal.inria.fr/hal-02401938
  • 11S. Deslauriers-Gauthier, J.-M. Lina, R. Butler, K. Whittingstall, P.-M. Bernier, R. Deriche, M. Descoteaux.

    White Matter Information Flow Mapping from Diffusion MRI and EEG, in: NeuroImage, July 2019. [ DOI : 10.1016/j.neuroimage.2019.116017 ]

    https://hal.inria.fr/hal-02187859
  • 12R. H. Fick, D. Wassermann, R. Deriche.

    The Dmipy Toolbox: Diffusion MRI Multi-Compartment Modeling and Microstructure Recovery Made Easy, in: Frontiers in Neuroinformatics, October 2019, vol. 13. [ DOI : 10.3389/fninf.2019.00064 ]

    https://hal.archives-ouvertes.fr/hal-02400877
  • 13P. 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, 2019. [ DOI : 10.1002/mrm.27601 ]

    https://hal.archives-ouvertes.fr/hal-01928734
  • 14P. Görlach, E. Hubert, T. Papadopoulo.

    Rational invariants of even ternary forms under the orthogonal group, in: Foundations of Computational Mathematics, 2019, vol. 19, pp. 1315-1361. [ DOI : 10.1007/s10208-018-9404-1 ]

    https://hal.inria.fr/hal-01570853
  • 15K. Maksymenko, M. Clerc, T. Papadopoulo.

    Fast Approximation of EEG Forward Problem and Application to Tissue Conductivity Estimation, in: IEEE Transactions on Medical Imaging, 2019, https://arxiv.org/abs/1810.04410, forthcoming. [ DOI : 10.1109/TMI.2019.2936921 ]

    https://hal.inria.fr/hal-01890242
  • 16L. J. O'Donnell, A. Daducci, D. Wassermann, C. Lenglet.

    Advances in computational and statistical diffusion MRI, in: NMR in Biomedicine, 2019, vol. 32, no 4, e3805. [ DOI : 10.1002/nbm.3805 ]

    https://hal.inria.fr/hal-02432249
  • 17M. Pizzolato, G. Gilbert, J.-P. Thiran, M. Descoteaux, R. Deriche.

    Adaptive phase correction of diffusion-weighted images, in: NeuroImage, October 2019, 116274 p. [ DOI : 10.1016/j.neuroimage.2019.116274 ]

    https://hal.archives-ouvertes.fr/hal-02402015
  • 18S. Rimbert, N. Gayraud, L. Bougrain, M. Clerc, S. Fleck.

    Can a Subjective Questionnaire Be Used as Brain-Computer Interface Performance Predictor?, in: Frontiers in Human Neuroscience, January 2019, vol. 12, 11 p. [ DOI : 10.3389/fnhum.2018.00529 ]

    https://hal.inria.fr/hal-01990935
  • 19S. Rimbert, P. Riff, N. Gayraud, D. Schmartz, L. Bougrain.

    Median Nerve Stimulation Based BCI: A New Approach to Detect Intraoperative Awareness During General Anesthesia, in: Frontiers in Neuroscience, June 2019, vol. 13, 13 p. [ DOI : 10.3389/fnins.2019.00622 ]

    https://hal.inria.fr/hal-02159777
  • 20M. Zucchelli, S. Deslauriers-Gauthier, R. Deriche.

    A Computational Framework For Generating Rotation Invariant Features And Its Application In Diffusion MRI, in: Medical Image Analysis, February 2020. [ DOI : 10.1016/j.media.2019.101597 ]

    https://hal.inria.fr/hal-02370077

International Conferences with Proceedings

  • 21A. Alimi, S. Deslauriers-Gauthier, R. Deriche.

    Towards validation of diffusion MRI tractography: bridging the resolution gap with 3D Polarized Light Imaging, in: ISMRM 2019 - 27th Annual Meeting of International Society for Magnetic Resonance in Medicine, Montréal, Canada, May 2019.

    https://hal.inria.fr/hal-02070912
  • 22A. Alimi, S. Deslauriers-Gauthier, F. Matuschke, D. Schmitz, M. Axer, R. Deriche.

    Analytical Fiber ODF Reconstruction in 3D Polarized Light Imaging: Performance Assessment, in: ISBI 2019 - IEEE International Symposium on Biomedical Imaging, Venice, Italy, 2019.

    https://hal.inria.fr/hal-01988262
  • 23S. Deslauriers-Gauthier, R. Deriche.

    Estimation of Axon Conduction Delay, Conduction Speed, and Diameter from Information Flow using Diffusion MRI and MEG, in: ISMRM 2019 - 27th Annual Meeting of International Society for Magnetic Resonance in Medicine, Montreal, Canada, May 2019, Data were provided by the Human Connectome Project (HCP), WU-MinnConsortium (Principal Investigators: David Van Essen and Kamil Ugurbil;1U54MH091657) funded by the 16 NIH Institutes and Centers that supportthe NIH Blueprint for Neuroscience Research; and by the McDonnell Center forSystems Neuroscience at Washington University.

    https://hal.inria.fr/hal-02074059
  • 24S. Deslauriers-Gauthier, R. Deriche.

    Estimation of Axonal Conduction Speed and the Inter Hemispheric Transfer Time using Connectivity Informed Maximum Entropy on the Mean, in: SPIE Medical Imaging 2019, San Diego, United States, February 2019.

    https://hal.inria.fr/hal-02063396
  • 25P. Filipiak, R. H. Fick, A. Petiet, M. Santin, A.-C. Philippe, S. Lehéricy, R. Deriche, D. Wassermann.

    Coarse-Grained Spatiotemporal Acquisition Design for Diffusion MRI, in: ISBI 2019 - IEEE International Symposium on Biomedical Imaging, Venice, Italy, April 2019.

    https://hal.inria.fr/hal-01973588
  • 26S. Rimbert, P. Guerci, N. Gayraud, C. Meistelman, L. Bougrain.

    Innovative Brain-Computer Interface based on motor cortex activity to detect accidental awareness during general anesthesia, in: IEEE SMC 2019 - IEEE International Conference on Systems, Man, and Cybernetics, Bari, Italy, October 2019.

    https://hal.inria.fr/hal-02166934

Conferences without Proceedings

  • 27I. Costantini, S. Deslauriers-Gauthier, R. Deriche.

    Deconvolution of fMRI Data using a Paradigm Free Iterative Approach based on Partial Differential Equations, in: OHBM 2019 - Organization for Human Brain Mapping Annual Meeting, Rome, Italy, June 2019.

    https://hal.archives-ouvertes.fr/hal-02071193
  • 28I. Costantini, S. Deslauriers-Gauthier, R. Deriche.

    Novel 4-D Algorithm for Functional MRI Image Regularization using Partial Differential Equations, in: ISMRM 2019 - 27th Annual Meeting of International Society for Magnetic Resonance in Medicine, Montréal, Canada, May 2019.

    https://hal.archives-ouvertes.fr/hal-02074345
  • 29M. Frigo, S. Deslauriers-Gauthier, D. Parker​, A. A. Ould Ismail, J. J. Kim, R. Verma, R. Deriche.

    Effects of tractography filtering on the topology and interpretability of connectomes, in: OHBM 2019 - Organization for Human Brain Mapping, Roma, Italy, June 2019.

    https://hal.archives-ouvertes.fr/hal-02056641
  • 30M. Pizzolato, R. Deriche, E. J. Canales-Rodriguez, J.-P. Thiran.

    Spatially Varying Monte Carlo Sure for the Regularization of Biomedical Images, in: ISBI 2019 - IEEE 16th International Symposium on Biomedical Imaging, Venice, Italy, IEEE, April 2019, pp. 1639-1642. [ DOI : 10.1109/ISBI.2019.8759338 ]

    https://hal.archives-ouvertes.fr/hal-02401132
  • 31M. Zucchelli, D. Parker​, S. Deslauriers-Gauthier, J. J. Kim, R. Verma​, R. Deriche.

    A Novel Characterization of Traumatic Brain Injury in White Matter with Diffusion MRI Spherical-Harmonics Rotation Invariants, in: ISMRM 2019 - 27th Annual Meeting of International Society for Magnetic Resonance in Medicine, Montreal, Canada, May 2019.

    https://hal.inria.fr/hal-02071315

Scientific Popularization

  • 32F. Turi, M. Clerc.

    Adaptive parameter setting in a code modulated visual evoked potentials BCI, in: 8th Graz Brain-Computer Interface Conference 2019, Graz, Austria, September 2019.

    https://hal.inria.fr/hal-02303562

Other Publications

  • 33J. Benerradi.

    Measuring auditory attention with electroencephalography, Université de Lorraine ; Inria - Sophia Antipolis, September 2019, 57 p.

    https://hal.inria.fr/hal-02285224
  • 34I. Kojčić, T. Papadopoulo, R. Deriche, S. Deslauriers-Gauthier.

    Connectivity-informed solution for spatio-temporal M/EEG source reconstruction, July 2019, NeuroMod 2019 - First meeting of the NeuroMod Institute, Poster.

    https://hal.inria.fr/hal-02279612
  • 35I. Kojčić, T. Papadopoulo, R. Deriche, S. Deslauriers-Gauthier.

    Connectivity-informed spatio-temporal MEG source reconstruction: Simulation results using a MAR model, October 2019, Colloque Line Garnero, Poster.

    https://hal.inria.fr/hal-02379744
  • 36F. Lotte, M. Clerc, A. Appriou, A. Audino, C. Benaroch, P. Giacalone, C. Jeunet, J. Mladenović, T. Monseigne, T. Papadopoulo, L. Pillette, A. Roc, K. Sadatnejad, F. Turi.

    Inria Research & Development for the Cybathlon BCI series, September 2019, 8th Graz Brain-Computer Interface Conference 2019, Poster.

    https://hal-univ-rennes1.archives-ouvertes.fr/hal-02433970
References in notes
  • 37H. Johansen-Berg, T. E. J. Behrens (editors)

    Diffusion MRI : From Quantitative Measurement to In vivo Neuroanatomy, Elevier - Academic Press, 2009.
  • 38D. K. Jones (editor)

    Diffusion MRI: Theory, Methods, and Applications, Oxford University Press, 2011.
  • 39Y. 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.
  • 40Y. 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
  • 41H.-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
  • 42H. 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.
  • 43A. 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
  • 44P. 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.
  • 45P. J. Basser, J. Mattiello, D. Le Bihan.

    MR Diffusion Tensor Spectroscopy and imaging, in: Biophysical Journal, 1994, vol. 66, no 1, pp. 259–267.
  • 46B. 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.
  • 47P. T. Callaghan.

    Principles of nuclear magnetic resonance microscopy, Oxford University Press, Oxford, 1991.
  • 48E. Caruyer.

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

    http://hal.inria.fr/tel-00750144
  • 49J. 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
  • 50R. 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
  • 51M. 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
  • 52M. 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
  • 53M. 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
  • 54M. 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
  • 55Q. 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.
  • 56P. 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.
  • 57A. 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
  • 58A. 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/
  • 59A. 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
  • 60A. 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
  • 61S. Hitziger, M. Clerc, S. Saillet, C. Bénar, T. Papadopoulo.

    Adaptive Waveform Learning: A Framework for Modeling Variability in Neurophysiological Signals, in: IEEE Transactions on Signal Processing, April 2017, vol. 65, no 16, pp. 4324–4338.

    http://dx.doi.org/10.1109/TSP.2017.2698415
  • 62J. 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
  • 63D. Le Bihan, E. Breton.

    Imagerie de Diffusion in vivo par Résonnance Magnétique Nucléaire, in: CR Académie des Sciences, 1985, no 301, pp. 1109-1112.
  • 64D. 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
  • 65C. 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
  • 66C. 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
  • 67L. 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.
  • 68K. Merboldt, W. Hanicke, J. Frahm.

    Self-diffusion NMR Imaging Using Stimulated Echoes, in: J. Magn. Reson., 1985, vol. 64, pp. 479–486.
  • 69S. Merlet.

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

    https://tel.archives-ouvertes.fr/tel-00908369/
  • 70I. 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.
  • 71E. 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
  • 72A.-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.
  • 73A.-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
  • 74T. 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
  • 75S. 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.
  • 76S. 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
  • 77E. 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.
  • 78D. G. Taylor, M. C. Bushell.

    The spatial mapping of translational diffusion coefficients by the NMR imaging technique, in: Phys. Med. Biol., 1985, vol. 30, pp. 345-349.

    https://iopscience.iop.org/article/10.1088/0031-9155/30/4/009
  • 79D. Tuch.

    Q-Ball Imaging, in: Magnetic Resonance in Medicine, 2004, vol. 52, no 6, pp. 1358–1372.
  • 80S. 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
  • 81V. 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.
  • 82H. Zhang, T. Schneider, C. A. Wheeler-Kingshott, D. C. Alexander.

    NODDI: Practical in vivo neurite orientation dispersion and density imaging of the human brain, in: NeuroImage, March 2012, vol. 61, pp. 1000–1016.

    http://dx.doi.org/10.1016/j.neuroimage.2012.03.072
  • 83E. Özarslan, C. G. Koay, T. M. Shepherd, S. J. Blackband, P. J. 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
  • 84E. Özarslan, C. G. Koay, T. M. Shepherd, M. E. Komlosh, M. O. 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.

    https://www.sciencedirect.com/science/article/pii/S1053811913003431
  • 85E. Özarslan, T. H. Mareci.

    Generalized Diffusion Tensor Imaging and Analytical Relationships Between Diffusion Tensor Imaging and High Angular Resolution Imaging, in: Magnetic Resonance in Medicine, 2003, vol. 50, pp. 955–965.
  • 86E. Özarslan, B. C. Vemuri, T. H. Mareci.

    Generalized Scalar Measures for Diffusion MRI Using Trace, Variance and Entropy, in: Magnetic Resonance in Medicine, 2005, vol. 53, no 4, pp. 866-876.


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