33 citations · 89 across the 29 of their papers we have counts for
10 papers · 1 filter
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…
An algorithm for variable density sampling with block-constrained acquisition
Claire Boyer, Pierre Weiss, Jérémie Bigot
Reducing acquisition time is of fundamental importance in various imaging modalities. The concept of variable density sampling provides a nice framework to achieve this. It was jus…
On Variant Strategies To Solve The Magnitude Least Squares Optimization Problem In Parallel Transmission Pulse Design And Under Strict SAR And Power Constraints
Andres Hoyos Idrobo, Pierre Weiss, Aurélien Massire +2
Parallel transmission has been a very promising candidate technology to mitigate the inevitable radio-frequency field inhomogeneity in magnetic resonance imaging (MRI) at ultra-hig…
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…
Variable Density Compressed Sensing In MRI. Theoretical vs Heuristic Sampling Strategies
Nicolas Chauffert, Philippe Ciuciu, Pierre Weiss
The structure of Magnetic Resonance Images (MRI) and especially their compressibility in an appropriate representation basis enables the application of the compressive sensing theo…