University Research Lecturer
- Royal Academy of Engineering Research Fellow
- Head of Image Reconstruction
My research focuses on the development of methods and techniques for speeding up the acquisition of functional magnetic resonance imaging (FMRI) data. This is important for providing large amounts of finely sampled temporal information about the brain in shorter durations, reducing imaging times and facilitating research on the brain's functional architecture and dynamics.
I am currently exploring methods for acceleration using low-rank constraints and 3D measurement techniques at 3T and 7T magnetic field strengths to improve resting state FMRI data collection efficiency.
The Set Increment with Limited Views Encoding Ratio (SILVER) Method for Optimizing Radial Sampling of Dynamic MRI
Schauman SS. et al, (2020)
High-Resolution Metabolic Mapping of the Cerebellum Using a Zoomed Magnetic Resonance Spectroscopic Imaging
Emir U. et al, (2020)
Methods for quantitative susceptibility and R2* mapping in whole post-mortem brains at 7T
Wang C. et al, (2020)
Highly accelerated vessel‐selective arterial spin labeling angiography using sparsity and smoothness constraints
Schauman SS. et al, (2020), Magnetic Resonance in Medicine, 83, 892 - 905
Improved statistical efficiency of simultaneous multi-slice fMRI by reconstruction with spatially adaptive temporal smoothing
Chiew M. and Miller KL., (2019), NeuroImage, 203, 116165 - 116165