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.
Improved statistical efficiency of simultaneous multi-slice fMRI by reconstruction with spatially adaptive temporal smoothing.
Chiew M. and Miller KL., (2019), Neuroimage
Highly Accelerated Vessel-Selective Arterial Spin Labelling Angiography using Sparsity and Smoothness Constraints
Schauman SS. et al, (2019), Magnetic Resonance in Medicine
Volume-localized measurement of oxygen extraction fraction in the brain using MRI.
O'Brien C. et al, (2019), Magn Reson Med
Recovering task fMRI signals from highly under-sampled data with low-rank and temporal subspace constraints.
Chiew M. et al, (2018), Neuroimage, 174, 97 - 110
Metabolite-cycled density-weighted concentric rings k-space trajectory (DW-CRT) enables high-resolution 1 H magnetic resonance spectroscopic imaging at 3-Tesla.
Steel A. et al, (2018), Sci Rep, 8