Richard Shaw
PhD student on the Medical Imaging CDT at UCL/KCL. Working on making deep learning models robust to poor quality data, specifically MRI k-space artefacts and patient movement artefacts. Using Bayesian neural networks to predict uncertainty estimates for tasks such as brain segmentation and artefact correction. Aiming to develop an automatic quality control system to provide real-time warning to such artefacts.
Projects
Neurology - DementiaCOVID-19
Uncertainty Modelling
Image Segmentation
Publications
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.
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.