10 citations · 21 across the 7 of their papers we have counts for
8 papers
A projection algorithm on measures sets
Nicolas Chauffert, Philippe Ciuciu, Jonas Kahn +1
We consider the problem of projecting a probability measure on a set of Radon measures. The projection is defined as a solution of the following variational pr…
Variable density sampling based on physically plausible gradient waveform. Application to 3D MRI angiography
Nicolas Chauffert, Pierre Weiss, Marianne Boucher +2
Performing k-space variable density sampling is a popular way of reducing scanning time in Magnetic Resonance Imaging (MRI). Unfortunately, given a sampling trajectory, it is not c…
Gradient waveform design for variable density sampling in Magnetic Resonance Imaging
Nicolas Chauffert, Pierre Weiss, Jonas Kahn +1
Fast coverage of k-space is a major concern to speed up data acquisition in Magnetic Resonance Imaging (MRI) and limit image distortions due to long echo train durations. The hardw…
Variable density sampling with continuous trajectories. Application to MRI
Nicolas Chauffert, Philippe Ciuciu, Jonas Kahn +1
Reducing acquisition time is a crucial challenge for many imaging techniques. Compressed Sensing (CS) theory offers an appealing framework to address this issue since it provides t…
From variable density sampling to continuous sampling using Markov chains
Nicolas Chauffert, Philippe Ciuciu, Pierre Weiss +1
Since its discovery over the last decade, Compressed Sensing (CS) has been successfully applied to Magnetic Reso- nance Imaging (MRI). It has been shown to be a powerful way to red…
Travelling salesman-based variable density sampling
Nicolas Chauffert, Philippe Ciuciu, Jonas Kahn +1
Compressed sensing theory indicates that selecting a few measurements independently at random is a near optimal strategy to sense sparse or compressible signals. This is infeasible…