28 citations · 32 across the 4 of their papers we have counts for
5 papers
Weakly Convex Ridge Regularization for 3D Non-Cartesian MRI Reconstruction
German Shâma Wache, Chaithya G R, Asma Tanabene +1
While highly accelerated non-Cartesian acquisition protocols significantly reduce scan time, they often entail long reconstruction delays. Deep learning based reconstruction method…
Hybrid learning of Non-Cartesian k-space trajectory and MR image reconstruction networks
Chaithya G R, Zaccharie Ramzi, Philippe Ciuciu
Compressed sensing (CS) in Magnetic resonance Imaging (MRI) essentially involves the optimization of 1) the sampling pattern in k-space under MR hardware constraints and 2) image r…
Optimizing full 3D SPARKLING trajectories for high-resolution T2*-weighted Magnetic Resonance Imaging
Chaithya G R, Pierre Weiss, Guillaume Daval-Frérot +3
The Spreading Projection Algorithm for Rapid K-space samplING, or SPARKLING, is an optimization-driven method that has been recently introduced for accelerated 2D T2*-w MRI using c…
Learning the sampling density in 2D SPARKLING MRI acquisition for optimized image reconstruction
Chaithya G R, Zaccharie Ramzi, Philippe Ciuciu
The SPARKLING algorithm was originally developed for accelerated 2D magnetic resonance imaging (MRI) in the compressed sensing (CS) context. It yields non-Cartesian sampling trajec…
PySAP: Python Sparse Data Analysis Package for Multidisciplinary Image Processing
S. Farrens, A. Grigis, L. El Gueddari +7
We present the open-source image processing software package PySAP (Python Sparse data Analysis Package) developed for the COmpressed Sensing for Magnetic resonance Imaging and Cos…