activity
20192022
collaborators

7 papers

physics.med-ph2022

Head-and-neck multi-channel B1+ mapping and carotid arteries RF shimming using a parallel transmit head coil

Matthijs H. S. de Buck, Peter Jezzard, Aaron T. Hess

Purpose: Neurovascular MRI suffers from a rapid drop in B1+ into the neck when using transmit head coils at 7T. One solution to improving B1+ magnitude in the major feeding arterie…

math.NA2022

Tuning-free multi-coil compressed sensing MRI with Parallel Variable Density Approximate Message Passing (P-VDAMP)

Charles Millard, Mark Chiew, Jared Tanner +2

Magnetic Resonance Imaging (MRI) has excellent soft tissue contrast but is hindered by an inherently slow data acquisition process. Compressed sensing, which reconstructs sparse si…

physics.med-ph2021

Optimization of Undersampling Parameters for 3D Intracranial Compressed Sensing MR Angiography at 7 Tesla

Matthijs H. S. de Buck, Peter Jezzard, Aaron T. Hess

Purpose: 3D Time-of-flight (TOF) MR Angiography (MRA) can accurately visualize the intracranial vasculature, but is limited by long acquisition times. Compressed sensing (CS) recon…

eess.IV2020

Accelerated calibrationless parallel transmit mapping using joint transmit and receive low-rank tensor completion

Aaron T Hess, Iulius Dragonu, Mark Chiew

Purpose: To evaluate an algorithm for calibrationless parallel imaging to reconstruct undersampled parallel transmit field maps for the body and brain. Methods: Using synthetic dat…

physics.med-ph2020

An investigation into the minimum number of tissue groups required for 7T in-silico parallel transmit electromagnetic safety simulations in the human head

Matthijs H. S. de Buck, Peter Jezzard, Hongbae Jeong +1

Purpose: Safety limits for the permitted Specific Absorption Rate (SAR) place restrictions on pulse sequence design, especially at ultra-high fields ( tesla). Due to inter-…

eess.SP2020

Approximate Message Passing with a Colored Aliasing Model for Variable Density Fourier Sampled Images

Charles Millard, Aaron T Hess, Boris Mailhé +1

The Approximate Message Passing (AMP) algorithm efficiently reconstructs signals which have been sampled with large i.i.d. sub-Gaussian sensing matrices. Central to AMP is its "sta…