Thomas Varsavsky
I’m a PhD student supervised by Prof. Parashkev Nachev at University College London and M. Jorge Cardoso at King’s College London. After finishing my BSc in Physics at Imperial College London I decided to do the Machine Learning MSc at UCL. I worked at Tractable, a computer vision company in London for 18 months before starting this PhD program in Jan 2018. I’m interested in automating various aspects of neuroradiology, with a focus on large messy clinical datasets and natural language processing of radiological report text.
Projects
Neurology - DementiaRadiology - Triaging
COVID-19
Image Segmentation
Domain Adaptation
Publications
Risk of COVID-19 among front-line health-care workers and the general community: a prospective cohort study
Nguyen, L.H., Drew, D.A., Graham, M.S., Joshi, A.D., Guo, C.G., Ma, W., Mehta, R.S., Warner, E.T., Sikavi, D.R., Lo, C.H. and Kwon, S., 2020. The Lancet Public Health.
Neuromorphologicaly-preserving Volumetric data encoding using VQ-VAE
Tudosiu, P.D., Varsavsky, T., Shaw, R., Graham, M., Nachev, P., Ourselin, S., Sudre, C.H. and Cardoso, M.J., 2020. arXiv preprint arXiv:2002.05692.
Automated Labelling using an Attention model for Radiology reports of MRI scans (ALARM)
Wood, D.A., Lynch, J., Kafiabadi, S., Guilhem, E., Busaidi, A.A., Montvila, A., Varsavsky, T., Siddiqui, J., Gadapa, N., Townend, M. and Kiik, M., 2020. arXiv preprint arXiv:2002.06588.
A k-Space Model of Movement Artefacts: Application to Segmentation Augmentation and Artefact Removal
Shaw, R., Sudre, C.H., Varsavsky, T., Ourselin, S. and Cardoso, M.J., 2020. IEEE Transactions on Medical Imaging.
Rapid implementation of mobile technology for real-time epidemiology of COVID-19
Drew, D.A., Nguyen, L.H., Steves, C.J., Menni, C., Freydin, M., Varsavsky, T., Sudre, C.H., Cardoso, M.J., Ourselin, S., Wolf, J. and Spector, T.D., 2020. Science.