452 citations · 933 across the 19 of their papers we have counts for
23 papers
MONAI: An open-source framework for deep learning in healthcare
M. Jorge Cardoso, Wenqi Li, Richard Brown +53
Artificial Intelligence (AI) is having a tremendous impact across most areas of science. Applications of AI in healthcare have the potential to improve our ability to detect, diagn…
Brain Imaging Generation with Latent Diffusion Models
Walter H. L. Pinaya, Petru-Daniel Tudosiu, Jessica Dafflon +5
Deep neural networks have brought remarkable breakthroughs in medical image analysis. However, due to their data-hungry nature, the modest dataset sizes in medical imaging projects…
Morphology-preserving Autoregressive 3D Generative Modelling of the Brain
Petru-Daniel Tudosiu, Walter Hugo Lopez Pinaya, Mark S. Graham +10
Human anatomy, morphology, and associated diseases can be studied using medical imaging data. However, access to medical imaging data is restricted by governance and privacy concer…
Acquisition-invariant brain MRI segmentation with informative uncertainties
Pedro Borges, Richard Shaw, Thomas Varsavsky +5
Combining multi-site data can strengthen and uncover trends, but is a task that is marred by the influence of site-specific covariates that can bias the data and therefore any down…
The role of MRI physics in brain segmentation CNNs: achieving acquisition invariance and instructive uncertainties
Pedro Borges, Richard Shaw, Thomas Varsavsky +5
Being able to adequately process and combine data arising from different sites is crucial in neuroimaging, but is difficult, owing to site, sequence and acquisition-parameter depen…
Deep forecasting of translational impact in medical research
Amy PK Nelson, Robert J Gray, James K Ruffle +10
The value of biomedical research--a $1.7 trillion annual investment--is ultimately determined by its downstream, real-world impact. Current objective predictors of impact rest on p…