Mark Chiew, PhD
Associate Professor
Royal Academy of Engineering Research Fellow
Wellcome Centre for Integrative Neuroimaging
Nuffield Department of Clinical Neurosciences
University of Oxford
Contact
Wellcome Trust Centre for Integrative Neuroimaging (FMRIB)
John Radcliffe Hospital
OX3 9DU
Oxford
United Kingdom
mark.chiew@ndcn.ox.ac.uk
+44 (0) 1865 611287
Research Summary
My research focuses on the development of data acquisition strategies and computational methods for reconstruction of magnetic resonance imaging data. My group works mostly in neuroimaging, at both 3 T and 7 T magnetic field strengths.
Some research themes include the development of 3D acquisition and sampling strategies for functional MRI, and the reconstruction of highly under-sampled MRI data using sparse and low-rank methods. We explore the application of computational imaging techniques to MRI for reducing acquisition times, improving spatial and/or temporal resolution, or improving robustness to physiological fluctuations or motion. In addition to fMRI, I am also interested in angiography and perfusion imaging with ASL, spectroscopic imaging, real-time MRI and multi-modal imaging.
Recent Publications
- Shahdloo M, Schüffelgen U, Papp D, Miller KL, Chiew M, “Model-based dynamic off-resonance correction for improved accelerated fMRI in awake behaving non-human primates”, bioRxiv 2021.09.23.461491 | preprint
- Shen X, Ozen A, Susnjar A, Ilbey S, Shi R, Chiew M, Emir UE, “Myelin Imaging Using 3D Dual-echo Ultra-short Echo Time MRI with Rosette k-Space Pattern”, bioRxiv 2021.09.18.460869 | preprint
- Chen X, Wu W, Chiew M, “Improving robustness of 3D multi-shot EPI by structured low-rank reconstruction of segmented CAIPI sampling for fMRI at 7T” bioRxiv 2021.08.19.457024 | preprint
- Clarke WT, Chiew M, “Uncertainty in denoising of MRSI using low-rank methods”, Magnetic Resonance in Medicine (Online Early View) | doi | preprint
- Mason HT, Graedel NN, Miller KL, Chiew M, “Subspace-constrained approaches to low-rank fMRI acceleration”, NeuroImage 2021 118235 | doi | preprint
Funding Sources
- Royal Academy of Engineering Research Fellowship (RF201617\16\23)
- Engineering and Physical Sciences Research Council (EP/T013133/1)