Publications (12)
Computational limits to the legibility of the imaged human brain
James K Ruffle, Robert J Gray, Samia Mohinta +5
Our knowledge of the organisation of the human brain at the population-level is yet to translate into power to predict functional differences at the individual-level, limiting clin…
Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy
Stanislav Nikolov, Sam Blackwell, Alexei Zverovitch +26
Over half a million individuals are diagnosed with head and neck cancer each year worldwide. Radiotherapy is an important curative treatment for this disease, but it requires manua…
Equitable modelling of brain imaging by counterfactual augmentation with morphologically constrained 3D deep generative models
Guilherme Pombo, Robert Gray, Jorge Cardoso +4
We describe Countersynth, a conditional generative model of diffeomorphic deformations that induce label-driven, biologically plausible changes in volumetric brain images. The mode…
Fast Unsupervised Brain Anomaly Detection and Segmentation with Diffusion Models
Walter H. L. Pinaya, Mark S. Graham, Robert Gray +12
Deep generative models have emerged as promising tools for detecting arbitrary anomalies in data, dispensing with the necessity for manual labelling. Recently, autoregressive trans…
An MRF-UNet Product of Experts for Image Segmentation
Mikael Brudfors, Yaël Balbastre, John Ashburner +4
While convolutional neural networks (CNNs) trained by back-propagation have seen unprecedented success at semantic segmentation tasks, they are known to struggle on out-of-distribu…
Individualized prescriptive inference in ischaemic stroke
Dominic Giles, Chris Foulon, Guilherme Pombo +8
The gold standard in the treatment of ischaemic stroke is set by evidence from randomized controlled trials, based on simple descriptions of presumptively homogeneous populations.…