21 citations · 63 across the 4 of their papers we have counts for
4 papers
Automated Labelling using an Attention model for Radiology reports of MRI scans (ALARM)
David A. Wood, Jeremy Lynch, Sina Kafiabadi +13
Labelling large datasets for training high-capacity neural networks is a major obstacle to the development of deep learning-based medical imaging applications. Here we present a tr…
Neuromorphologicaly-preserving Volumetric data encoding using VQ-VAE
Petru-Daniel Tudosiu, Thomas Varsavsky, Richard Shaw +5
The increasing efficiency and compactness of deep learning architectures, together with hardware improvements, have enabled the complex and high-dimensional modelling of medical vo…
Physics-informed brain MRI segmentation
Pedro Borges, Carole Sudre, Thomas Varsavsky +4
Magnetic Resonance Imaging (MRI) is one of the most flexible and powerful medical imaging modalities. This flexibility does however come at a cost; MRI images acquired at different…
3D multirater RCNN for multimodal multiclass detection and characterisation of extremely small objects
Carole H. Sudre, Beatriz Gomez Anson, Silvia Ingala +7
Extremely small objects (ESO) have become observable on clinical routine magnetic resonance imaging acquisitions, thanks to a reduction in acquisition time at higher resolution. De…