121 results on '"Philippe Ciuciu"'
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2. Non-Cartesian Non-Fourier FMRI Imaging for High-Resolution Retinotopic Mapping at 7 Tesla.
3. Wavelets in the Deep Learning Era.
4. Hybrid Learning of Non-Cartesian K-Space Trajectory and Mr Image Reconstruction Networks.
5. MC-PDNet: Deep Unrolled Neural Network For Multi-Contrast Mr Image Reconstruction From Undersampled K-Space Data.
6. Optimizing Full 3D SPARKLING Trajectories for High-Resolution Magnetic Resonance Imaging.
7. NC-PDNet: A Density-Compensated Unrolled Network for 2D and 3D Non-Cartesian MRI Reconstruction.
8. Density Compensated Unrolled Networks For Non-Cartesian MRI Reconstruction.
9. Learning the sampling density in 2D SPARKLING MRI acquisition for optimized image reconstruction.
10. Benchmarking Deep Nets MRI Reconstruction Models on the Fastmri Publicly Available Dataset.
11. Wavelets in the Deep Learning Era.
12. SHINE: SHaring the INverse Estimate from the forward pass for bi-level optimization and implicit models.
13. Results of the 2020 fastMRI Challenge for Machine Learning MR Image Reconstruction.
14. Calibrationless Oscar-Based Image Reconstruction in Compressed Sensing Parallel MRI.
15. Multifractal Analysis for Cumulant-Based Epileptic Seizure Detection in Eeg Time Series.
16. fMRI BOLD signal decomposition using a multivariate low-rank model.
17. Sparsity-based Blind Deconvolution of Neural Activation Signal in FMRI.
18. Fast Adaptive Scene Sampling for Single-Photon 3D Lidar Images.
19. Benchmarking learned non-Cartesian k-space trajectories and reconstruction networks.
20. Spatially regularized wavelet leader scale-free analysis of fMRI data.
21. Interpretable and stable prediction of schizophrenia on a large multisite dataset using machine learning with structured sparsity.
22. Scale-Free Functional Connectivity Analysis from Source Reconstructed MEG Data.
23. Analysis vs Synthesis-based Regularization for Combined Compressed Sensing and Parallel MRI Reconstruction at 7 Tesla.
24. Self-Calibrating Nonlinear Reconstruction Algorithms for Variable Density Sampling and Parallel Reception MRI.
25. Density Compensated Unrolled Networks for Non-Cartesian MRI Reconstruction.
26. Optimizing full 3D SPARKLING trajectories for high-resolution T2*-weighted Magnetic Resonance Imaging.
27. Is good old GRAPPA dead?
28. SHINE: SHaring the INverse Estimate from the forward pass for bi-level optimization and implicit models.
29. Spatially regularized multifractal analysis for fMRI data.
30. PyHRF: A Python Library for the Analysis of fMRI Data Based on Local Estimation of the Hemodynamic Response Function.
31. Denoising Score-Matching for Uncertainty Quantification in Inverse Problems.
32. XPDNet for MRI Reconstruction: an Application to the fastMRI 2020 Brain Challenge.
33. State-of-the-Art Machine Learning MRI Reconstruction in 2020: Results of the Second fastMRI Challenge.
34. Emergence of β and γ networks following multisensory training.
35. Structured Sparse Principal Components Analysis With the TV-Elastic Net Penalty.
36. Multivariate hurst exponent estimation in FMRI. Application to brain decoding of perceptual learning.
37. Multi-subject joint parcellation detection estimation in functional MRI.
38. Impact of perceptual learning on resting-state fMRI connectivity: A supervised classification study.
39. A Bayesian non-parametric hidden Markov random model for hemodynamic brain parcellation.
40. Anisotropic compressed sensing for non-Cartesian MRI acquisitions.
41. Physiological models comparison for the analysis of ASL FMRI data.
42. Variational Physiologically Informed Solution to Hemodynamic and Perfusion Response Estimation from ASL fMRI Data.
43. Comparison of Stochastic and Variational Solutions to ASL fMRI Data Analysis.
44. Calibration-Less Multi-Coil Compressed Sensing Magnetic Resonance Image Reconstruction Based on OSCAR Regularization.
45. Multivariate semi-blind deconvolution of fMRI time series.
46. On the Generation of Sampling Schemes for Magnetic Resonance Imaging.
47. A Projection Algorithm for Gradient Waveforms Design in Magnetic Resonance Imaging.
48. Decoding perceptual thresholds from MEG/EEG.
49. Multi-subject Bayesian Joint Detection and Estimation in fMRI.
50. Model selection for hemodynamic brain parcellation in FMRI.
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