Robert J. Gray

According to our database, Robert J. Gray authored at least 21 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Equitable modelling of brain imaging by counterfactual augmentation with morphologically constrained 3D deep generative models.

Guilherme Pombo, Robert J. Gray, M. Jorge Cardoso, Sébastien Ourselin, Geraint Rees, John Ashburner, Parashkev Nachev

Medical Image Anal., 2023

Compressed representation of brain genetic transcription.

James K. Ruffle, Henry C. Watkins, Robert J. Gray, Harpreet Hyare, Michel Thiebaut de Schotten, Parashkev Nachev

CoRR, 2023

The legibility of the imaged human brain.

James K. Ruffle, Robert J. Gray, Samia Mohinta, Guilherme Pombo, Chaitanya Kaul, Harpreet Hyare, Geraint Rees, Parashkev Nachev

CoRR, 2023

The minimal computational substrate of fluid intelligence.

Amy PK Nelson, Joe Mole, Guilherme Pombo, Robert J. Gray, James K. Ruffle, Edgar Chan, Geraint E. Rees, Lisa Cipolotti, Parashkev Nachev

CoRR, 2023

Patch-CNN: Training data-efficient deep learning for high-fidelity diffusion tensor estimation from minimal diffusion protocols.

Tobias Goodwin-Allcock, Ting Gong, Robert J. Gray, Parashkev Nachev, Hui Zhang

CoRR, 2023

Deep Variational Lesion-Deficit Mapping.

Guilherme Pombo, Robert J. Gray, Amy P. K. Nelson, Chris Foulon, John Ashburner, Parashkev Nachev

CoRR, 2023

InterSynth: A Semi-Synthetic Framework for Benchmarking Prescriptive Inference from Observational Data.

Dominic Giles, Robert J. Gray, Chris Foulon, Guilherme Pombo, Tianbo Xu, James K. Ruffle, Hans Rolf Jäger, Manuel Jorge Cardoso, Sébastien Ourselin, Geraint Rees, Ashwani Jha, Parashkev Nachev

Proceedings of the Machine Learning for Multimodal Healthcare Data, 2023

2022

3d_very_deep_vae.

Robert J. Gray, Matthew Graham, M. Jorge Cardoso, Sébastien Ourselin, Geraint Rees, Parashkev Nachev

Dataset, June, 2022

Deep forecasting of translational impact in medical research.

Amy P. K. Nelson, Robert J. Gray, James K. Ruffle, Henry C. Watkins, Daniel Herron, Nick Sorros, Danil Mikhailov, M. Jorge Cardoso, Sébastien Ourselin, Nick McNally, Bryan Williams, Geraint E. Rees, Parashkev Nachev

Patterns, 2022

Unsupervised brain imaging 3D anomaly detection and segmentation with transformers.

Walter H. L. Pinaya, Petru-Daniel Tudosiu, Robert J. Gray, Geraint Rees, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso

Medical Image Anal., 2022

How can spherical CNNs benefit ML-based diffusion MRI parameter estimation?

Tobias Goodwin-Allcock, Jason D. McEwen, Robert J. Gray, Parashkev Nachev, Hui Zhang

CoRR, 2022

Translating automated brain tumour phenotyping to clinical neuroimaging.

James K. Ruffle, Samia Mohinta, Robert J. Gray, Harpreet Hyare, Parashkev Nachev

CoRR, 2022

Fast Unsupervised Brain Anomaly Detection and Segmentation with Diffusion Models.

Walter H. L. Pinaya, Mark S. Graham, Robert J. Gray, Pedro F. Da Costa, Petru-Daniel Tudosiu, Paul Wright, Yee H. Mah, Andrew D. MacKinnon, James T. Teo, Hans Rolf Jäger, David Werring, Geraint Rees, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

How Can Spherical CNNs Benefit ML-Based Diffusion MRI Parameter Estimation?

Tobias Goodwin-Allcock, Jason D. McEwen, Robert J. Gray, Parashkev Nachev, Hui Zhang

Proceedings of the Computational Diffusion MRI - 13th International Workshop, 2022

2021

Hierarchical Graph-Convolutional Variational AutoEncoding for Generative Modelling of Human Motion.

Anthony Bourached, Robert J. Gray, Ryan-Rhys Griffiths, Ashwani Jha, Parashkev Nachev

CoRR, 2021

An artificial intelligence natural language processing pipeline for information extraction in neuroradiology.

Henry C. Watkins, Robert J. Gray, Ashwani Jha, Parashkev Nachev

CoRR, 2021

Unsupervised Brain Anomaly Detection and Segmentation with Transformers.

Walter Hugo Lopez Pinaya, Petru-Daniel Tudosiu, Robert J. Gray, Geraint Rees, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso

Proceedings of the Medical Imaging with Deep Learning, 7-9 July 2021, Lübeck, Germany., 2021

2020

Generative Model-Enhanced Human Motion Prediction.

Anthony Bourached, Ryan-Rhys Griffiths, Robert J. Gray, Ashwani Jha, Parashkev Nachev

CoRR, 2020

2019

Bayesian Volumetric Autoregressive Generative Models for Better Semisupervised Learning.

Guilherme Pombo, Robert J. Gray, Thomas Varsavsky, John Ashburner, Parashkev Nachev

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

2018

NiftyNet: a deep-learning platform for medical imaging.

Eli Gibson, Wenqi Li, Carole H. Sudre, Lucas Fidon, Dzhoshkun I. Shakir, Guotai Wang, Zach Eaton-Rosen, Robert J. Gray, Tom Doel, Yipeng Hu, Tom Whyntie, Parashkev Nachev, Marc Modat, Dean C. Barratt, Sébastien Ourselin, M. Jorge Cardoso, Tom Vercauteren

Comput. Methods Programs Biomed., 2018

2017

NiftyNet: a deep-learning platform for medical imaging.

Eli Gibson, Wenqi Li, Carole H. Sudre, Lucas Fidon, Dzhoshkun I. Shakir, Guotai Wang, Zach Eaton-Rosen, Robert J. Gray, Tom Doel, Yipeng Hu, Tom Whyntie, Parashkev Nachev, Dean C. Barratt, Sébastien Ourselin, M. Jorge Cardoso, Tom Vercauteren

CoRR, 2017