- 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.
Efficient 3D cone trajectory design for improved combined angiographic and perfusion imaging using arterial spin labeling
Shen Q. et al, (2024)
Self-navigated 3D diffusion MRI using an optimized CAIPI sampling and
structured low-rank reconstruction
Li Z. et al, (2024)
Multi-site Ultrashort Echo Time 3D Phosphorous MRSI repeatability using novel Rosette Trajectory (PETALUTE)
Alcicek S. et al, (2024)
Dynamic off-resonance correction improves functional image analysis in fMRI of awake behaving non-human primates
Shahdloo M. et al, (2023)
A Theoretical Framework for Self-Supervised MR Image Reconstruction Using Sub-Sampling via Variable Density Noisier2Noise.
Millard C. and Chiew M., (2023), IEEE Trans Comput Imaging, 9, 707 - 720