Author

Rachid Deriche B

Université Côte d'AzurORCID 0000-0002-4643-8417Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Neuroscience· 4

Signature Assays, Organisms & Methods

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Approach:statistical model· 4 Research Focus:benchmarking· 3 Organism:human· 3 Assay:imaging· 2 Approach:benchmark study· 1 Research Focus:clustering· 1 Research Focus:deconvolution· 1 Research Focus:differential expression· 1

Frequent Co-Authors

Samuel Deslauriers‐GauthieriD· 4 shared Matteo FrigoiD· 3 shared Mauro ZucchelliiD· 2 shared Rutger Fick· 2 shared Abib AlimiiD· 1 shared Alberto De LucaiD· 1 shared Alexander LeemansiD· 1 shared Andrada IanușiD· 1 shared

Activity by Year

2021-2021 · peak 4/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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4 shared papersNeuroscience

Samuel Deslauriers‐GauthierORCID

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Author profile →

4 papers

Recent·Most cited

On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: chronicles of the MEMENTO challenge.

Alberto De Luca, Andrada Ianuș, Alexander Leemans, Marco Palombo, Noam Shemesh, Hui Gary Zhang, Daniel C. Alexander, Markus Nilsson, Martijn Froeling, Geert Jan Biessels, Mauro Zucchelli, Matteo Frigo, Enes Albay, Sara Sedlar, Abib Alimi, , Kurt G. Schilling

NeuroImage · Jul 6, 2021Peer-reviewedNeuroscience

Network alignment and similarity reveal atlas-based topological differences in structural connectomes

Matteo Frigo, Emilio Cruciani, David Coudert A, Rachid Deriche B, Emanuele Natale, Samuel Deslauriers‐Gauthier

The paper introduces graph similarity measures and alignment techniques to evaluate atlas-based topological robustness in structural connectomes across subjects.

Network Neuroscience · May 21, 2021Peer-reviewedNeuroscience

A Paradigm Free Regularization Approach to Recover Brain Activation from Functional MRI Data

Isa Costantini, Rachid Deriche B, Samuel Deslauriers‐Gauthier

This paper introduces PF-fMRI, a paradigm-free method to recover brain activation from fMRI data without prior knowledge of the experimental paradigm, showing higher accuracy and faster computation than existing methods.

bioRxiv · Apr 14, 2021 · PreprintNeuroscience

Multi-Tissue Multi-Compartment models of diffusion MRI

Matteo Frigo, Rutger Fick, Mauro Zucchelli, Samuel Deslauriers‐Gauthier, Rachid Deriche B

This paper introduces a multi-tissue multi-compartment model for diffusion MRI using single-TE acquisitions, enabling analysis of previously acquired datasets.

bioRxiv · Jan 29, 2021 · PreprintNeuroscience