Philippe Ciuciu
Multidimensional Wavelet-based Regularized Reconstruction for Parallel Acquisition in Neuroimaging.
Wed, 01/04/2012 - 15:01 — SomNambulAuthors: Lotfi Chaari, Jean-Christophe Pesquet, Philippe Ciuciu, Sébastien Mériaux, Solveig Badillo
Subjects: Applications
AbstractParallel 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 reconstruction algorithm, which can proceed
either in the original k-space (GRAPPA, SMASH) or in the image domain
(SENSE-like methods). To improve the performance of the widely used SENSE
algorithm, 2D- or slice-specific regularization in the wavelet domain has been
deeply investigated.4D Wavelet-Based Regularization for Parallel MRI Reconstruction: Impact on Subject and Group-Levels Statistical Sensitivity in fMRI.
Mon, 03/21/2011 - 16:01 — SomNambulAuthors: Lotfi Chaari, Jean-Christophe Pesquet, Philippe Ciuciu, Sébastien Mériaux, Solveig Badillo
Subjects: Methodology
AbstractParallel MRI is a fast imaging technique that enables the acquisition of
highly resolved images in space. It relies on $k$-space undersampling and
multiple receiver coils with complementary sensitivity profiles in order to
reconstruct a full Field-Of-View (FOV) image. The performance of parallel
imaging mainly depends on the reconstruction algorithm, which can proceed
either in the original $k$-space (GRAPPA, SMASH) or in the image domain
(SENSE-like methods).ICA-based sparse feature recovery from fMRI datasets.
Mon, 06/14/2010 - 15:01 — SomNambulAuthors: Philippe Ciuciu, Gaël Varoquaux, Jean Baptiste Poline, Bertrand Thirion, Merlin Keller
Subjects: Applications
AbstractSpatial Independent Components Analysis (ICA) is increasingly used in the
context of functional Magnetic Resonance Imaging (fMRI) to study cognition and
brain pathologies. Salient features present in some of the extracted
Independent Components (ICs) can be interpreted as brain networks, but the
segmentation of the corresponding regions from ICs is still ill-controlled.
Here we propose a new ICA-based procedure for extraction of sparse features
from fMRI datasets. Specifically, we introduce a new thresholding procedure
that controls the deviation from isotropy in the ICA mixing model.An Iterative Method for Parallel MRI SENSE-based Reconstruction in the Wavelet Domain.
Thu, 09/03/2009 - 17:38 — SomNambulAuthors: Lotfi Chaari, Jean-Christophe Pesquet, Philippe Ciuciu, Amel Benazza-Benyahia
Subjects: Optimization and Control
AbstractTo reduce scanning time and/or improve spatial/temporal resolution in some
MRI applications, parallel MRI (pMRI) acquisition techniques with multiple
coils acquisition have emerged since the early 1990s as powerful 3D imaging
methods that allow faster acquisition of reduced Field of View (FOV) images. In
these techniques, the full FOV image has to be reconstructed from the resulting
acquired undersampled k-space data. To this end, several reconstruction
techniques have been proposed such as the widely-used SENSE method.An Iterative Method for Parallel MRI SENSE-based Reconstruction in the Wavelet Domain.
Thu, 09/03/2009 - 17:38 — SomNambulAuthors: Lotfi Chaari, Jean-Christophe Pesquet, Philippe Ciuciu, Amel Benazza-Benyahia
Subjects: Optimization and Control
AbstractTo reduce scanning time and/or improve spatial/temporal resolution in some
MRI applications, parallel MRI (pMRI) acquisition techniques with multiple
coils acquisition have emerged since the early 1990s as powerful 3D imaging
methods that allow faster acquisition of reduced Field of View (FOV) images. In
these techniques, the full FOV image has to be reconstructed from the resulting
acquired undersampled k-space data. To this end, several reconstruction
techniques have been proposed such as the widely-used SENSE method.
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