Philippe Ciuciu
Présentation
Philippe Ciuciu is Principal Investigator at NeuroSpin, the largest high field MRI center in France dedicated to cognitive and clinical neuroscience. His research interests are inter-disciplininary ranging from signal and image processing to functional brain imaging (fMRI, MEG) for applications to cognitive neuroscience (multi-perceptual learning, plasticity) and clinical trials in Alzheimer's disease and neurological disorders (Stroke). Magnetic resonance imaging (MRI): Compressed sensing, Variable density sampling, Parallel Imaging, k-space trajectories, High resolution (space/time) imaging, Reconstruction, Regularization, Proximal methods, Wavelets, Frames, parallel computing. Functional neuroimaging: Hemodynamics: functional MRI, Blood Oxygen Level Dependent, Cerebral blood flow, Arterial spin labelling, evoked activity, Detection-Estimation, Bayesian inference, MCMC, variational approximations, Functional brain parcellation. Scale-free brain dynamics: Magnetoencephalography (MEG), o ngoing activity, self-similarity, sequential neural processing, Multifractal Analysis, parallel neural multiplexing, functional connectivity, fractal connectivity.Research interests:
Industrial interests:
Publications
Publications
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Plug-and-Play reconstruction for 3D non-cartesian fMRI data33rd European Signal Processing Conference, EURASIP, Sep 2025, Palermo, Italy |
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Analyse multifractale construite sur les weak scaling exponentsGRETSI 2025 - XXXe Symposium Signal and Image Processing, Aug 2025, Strasbourg, France |
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Benchmarking 3D multi-coil NC-PDNET MRI reconstructionISMRM & ISMRT 2025 - Annual Meeting & Exhibition, May 2025, Honololu, Hawaii, United States |
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SNAKE-fMRI: A modular fMRI simulator from the space-time domain to k-space data and backISMRM 2024 - ISMRM & ISMRT Annual Meeting, ISMRM, May 2025, Singapour, Singapore |
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MRI-NUFFT: An open source Python package to make non-Cartesian MR Imaging easierISMRM & ISMRT 2025 - Annual Meeting & Exhibition, ISMRM, May 2025, Honolulu (Hawai), United States. ⟨10.58530/2024/4675⟩ |
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gGRAPPA: A Flexible, GPU-Accelerated Python Package for Fast and Efficient generalized GRAPPA ReconstructionISMRM & ISMRT 2025 - Annual Meeting & Exhibition, May 2025, Honololu, Hawaii, United States |
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Robust plug-and-play methods for highly accelerated non-Cartesian MRI reconstruction2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI), Apr 2025, Houston, France. pp.1-5, ⟨10.1109/ISBI60581.2025.10980851⟩ |
ECoG-Based Movement Classification and Limbs 3D Translation Prediction : a Deep Learning Study2025 International Joint Conference on Neural Networks (IJCNN), Jun 2025, Rome, France. pp.1-10, ⟨10.1109/IJCNN64981.2025.11228521⟩ |
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Bringing GRAPPA to non-Cartesian MRI through SPARKLING: An application to MPRAGE anatomical MRIISMRM & ISMRT 2025 - Annual Meeting & Exhibition, May 2025, Honololu, Hawaii, United States |
Machine Learning Models Trained in a Low-Dimensional Latent Space for Epileptogenic Zone (EZ) Localization2024 32nd European Signal Processing Conference (EUSIPCO), Aug 2024, Lyon, France. pp.1586-1590, ⟨10.23919/EUSIPCO63174.2024.10715112⟩ |
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Achieving high temporal resolution using a sliding-window approach for SPARKLING fMRI data: A simulation studyISMRM & ISMRT 2024 - Annual Meeting & Exhibition, ISMRM, May 2024, Singapore, Singapore |
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Denoising of FMRI volumes using local low rank methodsISBI 2023 - International Symposium on Biomedical Imaging, Apr 2023, Carthagena de India, Colombia. pp.1-5, ⟨10.1109/ISBI53787.2023.10230489⟩ |
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Impact of $\Delta \textrm{B}_0$ field imperfections correction on BOLD sensitivity in 3D-SPARKLING fMRI dataISMRM & ISMRT 2023 - Annual Meeting & Exhibition - Annual Meeting of the International Society for Magnetic Resonance in Medicine, International Society for Magnetic Resonance in Medicine, Jun 2023, Toronto, Canada |
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Non-Cartesian non-Fourier fmri imaging for high-resolution retinotopic mapping at 7 TeslaCAMSAP 2023 - IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, IEEE, Dec 2023, Los Suenos, Costa Rica |
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MC-PDNET: Deep unrolled neural network for multi-contrast mr image reconstruction from undersampled k-space dataISBI 2022 - IEEE International Symposium on Biomedical Imaging 2022, IEEE, Mar 2022, Kolkata, India |
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3D-SPARKLING for functional MRI: A pilot study for retinotopic mapping at 7TOHBM 2022, Jun 2022, Glasgow, United Kingdom |
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MORE-SPARKLING: non-cartesian trajectories with minimized off-resonance effectsJoint Annual Meeting ISMRM-ESMRMB & ISMRT 31st Annual Meeting, May 2022, London, United Kingdom |
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Hybrid learning of Non-Cartesian k-space trajectory and MR image reconstruction networksISBI 2022 - IEEE 19th International Symposium on Biomedical Imaging, IEEE, Mar 2022, Kolkata, India |
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Prospects of non-Cartesian 3D-SPARKLING encoding for functional MRI: A preliminary case study for retinotopic mappingJoint Annual Meeting ISMRM-ESMRMB & ISMRT 31st Annual Meeting, May 2022, London, United Kingdom |
Recent advances in electron tomography and applications in the semiconductor IndustryFCMN 2022 - International Conference on Frontiers of Characterization and Metrology for Nanoelectronics, Jun 2022, Monterey, United States |
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B0 field distortions monitoring and correction for 3D non-Cartesian fMRI acquisitions using a field camera: Application to 3D-SPARKLING at 7TJoint Annual Meeting ISMRM-ESMRMB & ISMRT 31st Annual Meeting, May 2022, London, United Kingdom |
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SHINE: SHaring the INverse Estimate from the forward pass for bi-level optimization and implicit modelsICLR 2022 - International Conference on Learning Representations, Apr 2022, Virtual, United States |
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Wavelets in the Deep Learning ERAEUSIPCO 2020 - 28th European Signal Processing Conference, Jan 2021, Amsterdam, Netherlands |
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Is good old GRAPPA dead?ISMRM 2021 - Annual Meeting of the International Society for Magnetic Resonance in Medicine, May 2021, Vancouver / Virtual, Canada |
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Off-resonance correction of non-Cartesian SWI using internal field map estimationInternational Society for Magnetic Resonance in Medicine, May 2021, Online, United States |
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Learning the sampling density in 2D SPARKLING MRI acquisition for optimized image reconstruction2021 29th European Signal Processing Conference (EUSIPCO), IEEE, Aug 2021, Dublin, Ireland |
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Benchmarking Deep Nets MRI Reconstruction Models on the FastMRI Publicly Available DatasetISBI 2020 - International Symposium on Biomedical Imaging, Apr 2020, Iowa City, United States |
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Denoising Score-Matching for Uncertainty Quantification in Inverse ProblemsNeurIPS 2020 - 34th Conference on Neural Information Processing Systems / Workshop on Deep Learning and Inverse Problems, Dec 2020, Vancouver / Virtuel, Canada |
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PySAP-MRI: a Python Package for MR Image ReconstructionISMRM workshop on Data Sampling and Image Reconstruction, Jan 2020, Sedona, AZ, United States |
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Online MR image reconstruction for compressed sensing acquisition in T2* imagingSPIE Conference - Wavelets and Sparsity XVIII, Aug 2019, San Diego, United States |
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fMRI BOLD signal decomposition using a multivariate low-rank modelEusipco 2019 - 27th European Signal Processing Conference, Sep 2019, Corunna, Spain |
3D SPARKLING for accelerated ex vivo T2*-weighted MRI with compressed sensingISMRM 2019 - 27th Annual Meeting & Exhibition, May 2019, Montréal, France |
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Benchmarking proximal methods acceleration enhancements for CS-acquired MR image analysis reconstructionSPARS 2019 - Signal Processing with Adaptive Sparse Structured Representations Workshop, Jul 2019, Toulouse, France |
OSCAR-based reconstruction for compressed sensing and parallel MR imagingISMRM 2019 - 27th Annual Meeting and Exhibition, May 2019, Montréal, Canada |
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Multifractal analysis for cumulant-based epileptic seizure detection in eeg time seriesISBI 2019 - IEEE International Symposium on Biomedical Imaging, Apr 2019, Venise, Italy |
Online compressed sensing MR image reconstruction for high resolution T2* imagingISMRM 2019 - 27th Annual Meeting and Exhibition, May 2019, Montréal, Canada |
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Sparsity-based blind deconvolution of neural activation signal in fMRIIEEE-ICASSP 2019 - International Conference on Acoustics, Speech and Signal Processing, May 2019, Brighton, United Kingdom |
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Distribution-controlled and optimally spread non-Cartesian sampling curves for accelerated in vivo brain imaging at 7 TeslaISMRM, Jun 2019, Paris, France |
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Fast adaptive scene sampling for single-photon 3D lidar imagesIEEE CAMSAP 2019 - International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, Dec 2019, Le Gosier (Guadeloupe), France |
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Calibrationless oscar-based image reconstruction in compressed sensing parallel MRIISBI 2019 - IEEE International Symposium on Biomedical Imaging, Apr 2019, Venise, Italy. ⟨10.1109/isbi.2019.8759393⟩ |
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Interpretable and stable prediction of schizophrenia on a large multisite dataset using machine learning with structured sparsity2018 International Workshop on Pattern Recognition in Neuroimaging (PRNI), Jun 2018, Singapore, Singapore. ⟨10.1109/PRNI.2018.8423946⟩ |
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Self-calibrating nonlinear reconstruction algorithms for variable density sampling and parallel reception MRI10th IEEE Sensor Array and Multichannel Signal Processing workshop, Jul 2018, Sheffield, United Kingdom. pp.1-5 |
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Scale-free functional connectivity analysis from source reconstructed MEG dataEUSIPCO 2018 - 26th European Signal Processing Conference, Sep 2018, Roma, Italy. pp.1-5 |
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Analysis vs Synthesis-based Regularization for combined Compressed Sensing and Parallel MRI Reconstruction at 7 Tesla26th European Signal Processing Conference (EUSIPCO 2018), Sep 2018, Roma, Italy |
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Spatially regularized wavelet leader scale-free analysis of fMRI dataIEEE International Symposium on Biomedical Imaging, Apr 2018, Washington, DC, United States |
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SPARKLING: Novel Non-Cartesian Sampling Schemes for Accelerated 2D Anatomical Imaging at 7T Using Compressed Sensing25th annua meeting of the International Society for Magnetic Resonance Imaging, Apr 2017, Honolulu, United States |
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SPARKLING: nouveaux schémas d’échantillonnage compressif prospectif pour l’IRM haute résolutionGRETSI, Sep 2017, Juan les Pins, France |
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Spatially regularized multifractal analysis for fMRI DataEMBC’17 - 39th International Conference of the IEEE Engineering in Medicine and Biology Society, Kwang Suk Park, Jul 2017, Jeju, South Korea. pp.4 |
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PyHRF: A Python Library for the Analysis of fMRI Data Based on Local Estimation of the Hemodynamic Response Function16th Python in Science Conference (SciPy 2017), Jul 2017, Austin, TX, United States. pp.34-40, ⟨10.25080/shinma-7f4c6e7-006⟩ |
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Multivariate Hurst Exponent Estimation in FMRI. Application to Brain Decoding of Perceptual Learning13th IEEE International Symposium on Biomedical Imaging, Apr 2016, Prague, Czech Republic |
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Impact of perceptual learning on resting-state fMRI connectivity: A supervised classification studyEusipco 2016, Aug 2016, Budapest, Hungary |
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Multi-subject joint parcellation detection estimation in functional MRI13th IEEE International Symposium on Biomedical Imaging, Apr 2016, Prague, Czech Republic. pp.74-77, ⟨10.1109/ISBI.2016.7493214⟩ |
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Comment représenter une image avec un spaghetti ?GRETSI, Sep 2015, Lyon, France |
Méthode d'approximation variationnelle pour l'analyse de données d'IRM fonctionnelle acquise par Arterial Spin LabellingGRETSI, Sep 2015, Lyon, France |
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Variable density sampling based on physically plausible gradient waveform. Application to 3D MRI angiographyIEEE International Symposium on Biomedical Imaging (ISBI), Apr 2015, New-York, United States |
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Sur la génération de schémas d'échantillonnage compressé en IRMGRETSI, Patrice Abry; Paulo Gonçalves, Sep 2015, Lyon, France. pp.4 |
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Comparison of Stochastic and Variational Solutions to ASL fMRI Data AnalysisMedical Image Computing and Computer-Assisted Intervention - MICCAI 2015, Oct 2015, Munich, Germany. pp.85-92, ⟨10.1007/978-3-319-24553-9_11⟩ |
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Variational Physiologically Informed Solution to Hemodynamic and Perfusion Response Estimation from ASL fMRI Data2015 International Workshop on Pattern Recognition in NeuroImaging, Jun 2015, Stanford, CA, United States. pp.57-60, ⟨10.1109/PRNI.2015.12⟩ |
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Physiological models comparison for the analysis of ASL FMRI data12th IEEE International Symposium on Biomedical Imaging, ISBI 2015, Apr 2015, New York, United States. pp.1348-1351, ⟨10.1109/ISBI.2015.7164125⟩ |
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La convergence de l'activité neurale vers des attracteurs multifractals localisés prédit la capacité d'apprentissageGRETSI, Sep 2015, Lyon, France |
Physiologically informed Bayesian analysis of ASL fMRI dataStatistical Challenges in Neuroscience workshop, Sep 2014, Warwick, United Kingdom |
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Model Selection for Hemodynamic Brain Parcellation in fMRIEUSIPCO - 22nd European Signal Processing Conference, Sep 2014, Lisbon, Portugal. pp.31 - 35 |
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Physiologically Informed Bayesian Analysis of ASL fMRI DataBAMBI 2014 - First International Workshop on Bayesian and grAphical Models for Biomedical Imaging, Sep 2014, Boston, United States. pp.37 - 48, ⟨10.1007/978-3-319-12289-2_4⟩ |
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Decoding perceptual thresholds from MEG/EEGPattern Recoginition in Neuroimaging (PRNI) (2014), Jun 2014, Tubingen, Germany. p00 |
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Hemodynamically informed parcellation of cerebral FMRI dataICASSP 2014 - 2014 IEEE International Conference on Acoustics, Speech and Signal Processing, May 2014, Florence, Italy. pp.2079-2083, ⟨10.1109/ICASSP.2014.6853965⟩ |
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Bayesian BOLD and perfusion source separation and deconvolution from functional ASL imagingICASSP 2013 - IEEE International Conference on Acoustics, Speech, and Signal Processing, May 2013, Vancouver, Canada. pp.1003-1007, ⟨10.1109/ICASSP.2013.6637800⟩ |
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Travelling salesman-based variable density samplingSampTA - 10th Conference International Conference on Sampling Theory and Applications, Jul 2013, Bremen, Germany. pp.509-512 |
Analyse parcimonieuse des données d'IRM fonctionnelle dans un cadre bayésien variationnel45èmes Journées de Statistique, Société Française de Statistique, May 2013, Toulouse, France |
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Variable Density Compressed Sensing In MRI. Theoretical vs Heuristic Sampling StrategiesISBI - 10th International Symposium on Biomedical Imaging, Apr 2013, San Francisco, United States |
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Hemodynamic estimation based on Consensus ClusteringPRNI 2013 -- 3rd International Workshop on Pattern Recognition in NeuroImaging, Jun 2013, Philadelphia, United States |
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Learning-induced modulation of scale-free properties of brain activity measured with MEG10th IEEE International Symposium on Biomedical Imaging, IEEE, Apr 2013, San Francisco, United States. pp.998-1001, ⟨10.1109/ISBI.2013.6556645⟩ |
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From variable density sampling to continuous sampling using Markov chainsSampTA - 10th Conference International Conference on Sampling Theory and Applications, Jul 2013, Bremen, Germany. pp.200-203 |
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Multi-session extension of the joint-detection framework in fMRIISBI 2013 - International Symposium on BIomedical Imaging: From Nano to Macro, Apr 2013, San Fransisco, United States. pp.1512-1515, ⟨10.1109/ISBI.2013.6556822⟩ |
A complex-valued majorize-minimize memory gradient method with application to parallel MRI21st European Signal Processing Conference (EUSIPCO 2013), Sep 2013, Marrakech, Morocco. pp.14283743.1-14283743.5 |
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Variational Variable Selection To Assess Experimental Condition Relevance In Event-Related fMRIISBI 2013 - 10th IEEE International Symposium on Biomedical Imaging, Apr 2013, San Francisco, United States. pp.1508-1511, ⟨10.1109/ISBI.2013.6556821⟩ |
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Bayesian Joint Detection-Estimation of cerebral vasoreactivity from ASL fMRI dataMICCAI 2013 - 16th International Conference on Medical Image Computing and Computer Assisted Intervention, Scientific Council of Japan, Sep 2013, Nagoya, Japan. pp.616-623, ⟨10.1007/978-3-642-40763-5_76⟩ |
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Robust voxel-wise Joint Detection Estimation of Brain Activity in fMRIICIP 2012 - 19th IEEE International Conference on Image Processing, Sep 2012, Orlando, United States. pp.1273-1276, ⟨10.1109/ICIP.2012.6467099⟩ |
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MODULATION OF SCALE-FREE PROPERTIES OF BRAIN ACTIVITY IN MEGIEEE International Symposium on Biomedical Imaging, May 2012, Barcelone, Spain. pp.1531--1534 |
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Adaptive experimental condition selection in event-related fMRIISBI 2012 - IEEE International Symposium on Biomedical Imaging, May 2012, Barcelone, Spain. pp.1755-1758, ⟨10.1109/ISBI.2012.6235920⟩ |
Sélection de variables dans un cadre Bayésien de traitement de données d'IRM fonctionnelle44e Journées de Statistique, Société Française de Statistique, May 2012, Bruxelles, Belgique |
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HYR2PICS: Hybrid Regularized Reconstruction for combined Parallel Imaging and Compressive Sensing in MRIIEEE International Symposium on Biomedical Imaging, May 2012, Barcelone, Spain |
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Hemodynamic-informed parcellation of fMRI data in a Joint Detection Estimation frameworkMICCAI 2012 - 15th International Conference on Medical Image Computing and Computer-Assisted Intervention, Oct 2012, Nice, France. pp.180-188, ⟨10.1007/978-3-642-33454-2_23⟩ |
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IMPACT OF THE JOINT DETECTION-ESTIMATION APPROACH ON RANDOM EFFECTS GROUP STUDIES IN FMRI2011 IEEE International Symposium on Biomedical Imaging: from Macro to Nano, Mar 2011, Chicago, United States. pp.1811 |
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Variational solution to the joint detection estimation of brain activity in fMRIMICCAI 2011 - 14th International Conference on Medical Image Computing and Computer-Assisted Intervention, Sep 2011, Toronto, Canada. pp.260-268, ⟨10.1007/978-3-642-23629-7_32⟩ |
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Image reconstruction from multiple sensors using Stein's principle. Application to parallel MRIISBI 2011, Mar 2011, United States |
A Variational Bayesian approach for the Joint Detection Estimation of Brain Activity in functional MRI43èmes Journées de Statistique, Société Française de Statistique (SFdS), May 2011, Tunis, Tunisia |
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Impact of the joint detection-estimation approach on random effects group studies in fMRIISBI 2011 - IEEE Computer Society International Symposium on Biomedical Imaging: From Nano to Macro, Mar 2011, Chicago, United States. pp.376-380, ⟨10.1109/ISBI.2011.5872427⟩ |
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MULTIFRACTAL ANALYSIS OF RESTING STATE NETWORKS IN FUNCTIONAL MRIIEEE International Symposium on Biomedical Imaging, Mar 2011, Chicago, United States. paper ID 1544 |
Bayesian variational approximation for the joint detection estimation of brain activity in fMRISSP 2011 - IEEE Statistical Signal Processing Workshop, Jun 2011, Nice, France. pp.469-472, ⟨10.1109/SSP.2011.5967734⟩ |
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A hierarchical Bayesian model for frame representationIEEE International Conference Acoustics, Speech, and Signal (ICASSP), Mar 2010, Dallas, USA, France. pp.4086-4089 |
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ICA-based sparse feature recovery from fMRI datasetsBiomedical Imaging, IEEE International Symposium on, Apr 2010, Rotterdam, Netherlands. pp.1177 |
How to deal with brain deactivations in the joint detection-estimation framework?HBM 2010 - Humain Brain Mapping conference, Jun 2010, Barcelone, Spain |
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Minimization of a sparsity promoting criterion for the recovery of complex-valued signalsSPARS'09 - Signal Processing with Adaptive Sparse Structured Representations, Inria Rennes - Bretagne Atlantique, Apr 2009, Saint Malo, France |
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SPATIALLY UNSUPERVISED ANALYSIS OF WITHIN-SUBJECT FMRI DATA USING MULTIPLE EXTRAPOLATIONS OF 3D ISING FIELD PARTITION FUNCTIONS2009 IEEE INTERNATIONAL WORKSHOP ON MACHINE LEARNING FOR SIGNAL PROCESSING (MLSP 2009), Sep 2009, Grenoble, France. pp.103-108 |
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Robust Extrapolation Scheme for Fast Estimation of 3D Ising Field Partition Functions: Application to Within-Subject fMRI Data Analysis12th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2009), Sep 2009, Londres, United Kingdom. pp.975-983 |
Autocalibrated regularized parallel MRI reconstruction in the waveletIEEE International Symposium on Biomedical Imaging (ISBI'08), May 2008, Paris, France, France. pp.756-759 |
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Spatial mixture modelling for the joint detection-estimation of brain activity in fMRIICASSP, Apr 2007, Honolulu, HA, United States. pp.325-328 |
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Application du rééchantillonnage stochastique de l'échelle en détection-estimation de l'activité cérébrale par IRMfColloque GRETSI, Sep 2007, France. pp 373-376 |
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Modeling non-linear and non-stationary effects of the BOLD response using mixture models in fMRIHuman Brain Mapping (12th Annual Meeting), Jun 2007, Florence, Italy |
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Mélanges spatiaux pour la détection-estimation conjointe de l'activité cérébrale en imagerie fonctionnelle (IRMf)Gretsi, Sep 2007, Troyes, France. pp.133-136 |
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Bayesian joint detection-estimation of brain activity using MCMC with a Gamma-Gaussian mixture prior modelICASSP, May 2006, Toulouse, France. pp.1093-1096 |
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Joint detection-estimation of brain activity in fMRI using an autoregressive noise model2006 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Apr 2006, Arlington, VA, United States. pp.1048-1051 |
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Model Based Spatial and Temporal Similarity Measures between Series of Functional Magnetic Resonance ImagesMedical Image Computing and Computer-Assisted Intervention (MICCAI'02), 2002, Tokyo, Japan. pp.509--516 |
Joint Detection-Estimation in Functional MRIJean-François Giovannelli; Jérôme Idier. Regularization and Bayesian Methods for Inverse Problems in Signal and Image Processing, John Wiley and Sons, pp.169-200, 2015, 978-1-84821-637-2. ⟨10.1002/9781118827253.ch7⟩ |
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Détection-estimation conjointe en IRM fonctionnelleJean-François Giovannelli and Jérôme Idier. Méthodes d'inversion appliquées au traitement du signal et de l'image, Hermès, 2013 |
method and apparatus for accelerated magnetic resonance imagingFrance, Patent n° : US2020/0205692. 2020 |
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Method for performing parallel magnetic resonance imagingFrance, Patent n° : PCT/IB2011/002330. 2012 |
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Spatio-temporal regularized reconstruction for parallel MRI acquisition systemsFrance, Patent n° : PCT/IB2011/002330. 2012 |
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MÉTHODES MARKOVIENNES EN ESTIMATION SPECTRALE NON PARAMETRIQUES. APPLICATION EN IMAGERIE RADAR DOPPLERAutre. Université Paris Sud - Paris XI, 2000. Français. ⟨NNT : ⟩ |
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Dynamique cérébrale en neuroimagerie fonctionnelleAutre [q-bio.OT]. Université Paris Sud - Paris XI, 2008 |