Research Fellow
- About
-
- Email Address
- vasiliki.mallikourti@abdn.ac.uk
- School/Department
- School of Medicine, Medical Sciences and Nutrition
Biography
Dr Mallikourti graduated from the University of Athens in 2004 with a BSc (Hons) in Physics. She moved to the University of Aberdeen to undertake an MSc in Medical Physics in 2015. She then stayed in Aberdeen to undertake a PhD in Medical Physics, investigating signal acquisition and processing algorithms for lipid composition measurement in breast cancer using a clinical 3T MRI system.
Following the award of her PhD in 2020, she joined the University of Aberdeen Field-cycling Imaging Group as a postdoctoral Research Fellow to investigate the extend Field Cycling Imaging can detect stroke, breast cancer and brain lesions.
Dr Mallikourti also joined the University of Aberdeen Biomedical Imaging Centre in January 2022 as a Research Fellow and co-applicant to investigate the measurement of brain glucose metabolism using Chemical Exchange Saturation Transfer (CEST) in patients with Alzheimer’s disease using the 3T MRI system.
In 2024, Dr Mallikourti launched a new pilot research study to investigate MRI methods for measuring brain glucosamine metabolism.
Qualifications
- MSc Medical Physics2016 - University of Aberdeen
- PhD in Medical Physics2020 - University of Aberdeen
Internal Memberships
Aberdeen Biomedical Imaging Centre (ABIC)
Latest Publications
Field cycling imaging to characterise breast cancer at low and ultra-low magnetic fields below 0.2 T
Communications Medicine, vol. 4, no. 1, pp. 221Contributions to Journals: Articles- [ONLINE] DOI: https://doi.org/10.1038/s43856-024-00644-2
Field-Cycling MRI for Identifying Minor Ischemic Stroke Below 0.2 T
Radiology, vol. 312, no. 2, e232972Contributions to Journals: ArticlesAssessing severity of cerebral small vessel disease using field-cycling MRI and automated segmentation
World Stroke Congress 2023, pp. 209Contributions to Journals: Abstracts- [ONLINE] DOI: https://doi.org/10.1177/17474930231192010
Detection of cerebral small vessel disease using denoised field-cycling MRI: Book of Abstracts ESMRMB 2023
Magnetic Resonance Materials in Physics, Biology and Medicine, vol. 36, no. Suppl 1, pp. s297Contributions to Journals: Abstracts- [ONLINE] DOI: https://doi.org/10.1007/s10334-023-01130-x
Automated segmentation of cerebral small vessel disease from field-cycling MRI: Proffered Conference Abstract - MIUA 2023
Chapters in Books, Reports and Conference Proceedings: Conference Proceedings