Within-subject analysis in fMRI essentially addresses two problems, the detection of brain
regions eliciting evoked activity and the estimation of the underlying dynamics. In Makni …

In this paper we present a novel wavelet-based Bayesian nonparametric regression model
for the analysis of functional magnetic resonance imaging (fMRI) data. Our goal is to provide …

Background Parallel magnetic resonance imaging (MRI) is a fast imaging technique that
helps acquiring highly resolved images in space/time. Its performance depends on the …

In this paper, we propose a fast numerical scheme to estimate Partition Functions (PF) of
symmetric Potts fields. Our strategy is first validated on 2D two-color Potts fields and then on …

Parallel computing resources are now available everywhere, from a simple multiple core
laptop to sophisticated clusters and grids. Soma-workflow originated in the observation that …

Parallel MRI is a fast imaging technique that enables the acquisition of highly resolved
images in space or/and in time. The performance of parallel imaging strongly depends on …

The paper presents a method for estimating the parameter of a Potts model jointly with the
unknowns of an image segmentation problem. The method addresses piecewise constant …

In an event-related functional MRI data analysis, an accurate and robust extraction of the
hemodynamic response function (HRF) and its associated statistics (eg, magnitude, width …

PMRI is a fast imaging technique that allows reconstruction of full FoV images based on
undersampled k-space data acquired using multiple reciever coils with complementary …

The paper tackles the problem of joint deconvolution and segmentation specifically for
textured images. The images are composed of patches of textures that belong to a set of K …