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 image 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
- Mason HT, Graedel NN, Miller KL, Chiew M, “Subspace-constrained approaches to low-rank fMRI acceleration”, bioRxiv 2020.12.15.422908 | preprint
- Hess AT, Dragonu I, Chiew M, “Accelerated calibrationless parallel transmit mapping using joint transmit and receive low-rank tensor completion”, arXiv:2011.06471 | preprint
- Wiltshire CEE, Chiew M, Chesters J, Mairead PH, Watkins KE “Speech movement variability in people who stutter: a vocal-tract MRI study”, PsyArXiv 2020; | preprint
- Schauman SS, Okell TW, Chiew M, “The Set Increment with Limited Views Encoding Ratio (SILVER) Method for Optimizing Radial Sampling of Dynamic MRI”, bioRxiv 2020.06.25.171017 | preprint
- Emir U, Sood J, Chiew M, Thomas MA, Lane S, “High-Resolution Metabolic Mapping of the Cerebellum Using 2D Zoom Magnetic Resonance Spectroscopic Imaging”, Magnetic Resonance in Medicine 2020; | doi | preprint
Funding Sources
- Royal Academy of Engineering Research Fellowship (RF201617\16\23)
- Engineering and Physical Sciences Research Council (EP/T013133/1)