Enantiomorphic normalization of focally lesioned brains. - Parashkev Nachev; Elizabeth J. Coulthard; Hans Rolf Jäger; Christopher Kennard; Masud Husain (NeuroImage, 2008)

The blind executive. - Parashkev Nachev (NeuroImage, 2011)

VTrails: Inferring Vessels with Geodesic Connectivity Trees. - Stefano Moriconi; Maria A. Zuluaga; Hans Rolf Jäger; Parashkev Nachev; Sébastien Ourselin; M. Jorge Cardoso (IPMI, 2017)

NiftyNet: a deep-learning platform for medical imaging. - Eli Gibson; Wenqi Li 001; Carole H. Sudre; Lucas Fidon; Dzhoshkun I. Shakir; Guotai Wang; Zach Eaton-Rosen; Robert J. Gray; Tom Doel; Yipeng Hu; Tom Whyntie; Parashkev Nachev; et al. (CoRR, 2017)

Comparing GABA-dependent physiological measures of inhibition with proton magnetic resonance spectroscopy measurement of GABA using ultra-high-field MRI. - Katherine Dyke; Sophia E. Pépés; Chen Chen; Soyoung Kim; Hilmar P. Sigurdsson; Amelia Draper; Masud Husain; Parashkev Nachev; Penelope A. Gowland; Peter G. Morris; Stephen R. Jackson (NeuroImage, 2017)

Elastic Registration of Geodesic Vascular Graphs. - Stefano Moriconi; Maria A. Zuluaga; Hans Rolf Jäger; Parashkev Nachev; Sébastien Ourselin; M. Jorge Cardoso (MICCAI (1), 2018)

PIMMS: Permutation Invariant Multi-modal Segmentation. - Thomas Varsavsky; Zach Eaton-Rosen; Carole H. Sudre; Parashkev Nachev; M. Jorge Cardoso (DLMIA/ML-CDS@MICCAI, 2018)

MRI Super-Resolution Using Multi-channel Total Variation. - Mikael Brudfors; Yaël Balbastre; Parashkev Nachev; John Ashburner (MIUA, 2018)

NiftyNet: a deep-learning platform for medical imaging. - Eli Gibson; Wenqi Li 001; Carole H. Sudre; Lucas Fidon; Dzhoshkun I. Shakir; Guotai Wang; Zach Eaton-Rosen; Robert J. Gray; Tom Doel; Yipeng Hu; Tom Whyntie; Parashkev Nachev; et al. (Comput. Methods Programs Biomed., 2018)

Lost in translation. - Parashkev Nachev; Geraint Rees 001; Richard S. Frackowiak (F1000Research, 2018)

Empirical Bayesian Mixture Models for Medical Image Translation. - Mikael Brudfors; John Ashburner; Parashkev Nachev; Yaël Balbastre (SASHIMI@MICCAI, 2019)

Towards Quantifying Neurovascular Resilience. - Stefano Moriconi; Rafael Rehwald; Maria A. Zuluaga; Hans Rolf Jäger; Parashkev Nachev; Sébastien Ourselin; M. Jorge Cardoso (MLMECH/CVII-STENT@MICCAI, 2019)

Multi-domain Adaptation in Brain MRI Through Paired Consistency and Adversarial Learning. - Mauricio Orbes-Arteaga; Thomas Varsavsky; Carole H. Sudre; Zach Eaton-Rosen; Lewis J. Haddow; Lauge Sørensen; Mads Nielsen; Akshay Pai; Sébastien Ourselin; Marc Modat; Parashkev Nachev; M. Jorge Cardoso (DART/MIL3ID@MICCAI, 2019)

Bayesian Volumetric Autoregressive Generative Models for Better Semisupervised Learning. - Guilherme Pombo; Robert J. Gray; Thomas Varsavsky; John Ashburner; Parashkev Nachev (MICCAI (4), 2019)

A Tool for Super-Resolving Multimodal Clinical MRI. - Mikael Brudfors; Yaël Balbastre; Parashkev Nachev; John Ashburner (CoRR, 2019)

Unsupervised Videographic Analysis of Rodent Behaviour. - Anthony Bourached; Parashkev Nachev (CoRR, 2019)

High-dimensional detection of imaging response to treatment in multiple sclerosis. - Baris Kanber; Parashkev Nachev; Frederik Barkhof; Alberto Calvi; Jorge Cardoso 002; Rosa Cortese; Ferran Prados; Carole H. Sudre; Carmen Tur; Sébastien Ourselin; Olga Ciccarelli (npj Digit. Medicine, 2019)

Author Correction: High-dimensional detection of imaging response to treatment in multiple sclerosis. - Baris Kanber; Parashkev Nachev; Frederik Barkhof; Alberto Calvi; Jorge Cardoso 002; Rosa Cortese; Ferran Prados; Carole H. Sudre; Carmen Tur; Sébastien Ourselin; Olga Ciccarelli (npj Digit. Medicine, 2019)

Redefining the research hospital. - Parashkev Nachev; Daniel Herron; Nick McNally; Geraint Rees 001; Bryan Williams (npj Digit. Medicine, 2019)

Predicting scheduled hospital attendance with artificial intelligence. - Amy P. K. Nelson; Daniel Herron; Geraint Rees 001; Parashkev Nachev (npj Digit. Medicine, 2019)

Inference of Cerebrovascular Topology With Geodesic Minimum Spanning Trees. - Stefano Moriconi; Maria A. Zuluaga; Hans Rolf Jäger; Parashkev Nachev; Sébastien Ourselin; M. Jorge Cardoso (IEEE Trans. Medical Imaging, 2019)

Flexible Bayesian Modelling for Nonlinear Image Registration. - Mikael Brudfors; Yaël Balbastre; Guillaume Flandin; Parashkev Nachev; John Ashburner (MICCAI (3), 2020)

Hierarchical Brain Parcellation with Uncertainty. - Mark S. Graham; Carole H. Sudre; Thomas Varsavsky; Petru-Daniel Tudosiu; Parashkev Nachev; Sébastien Ourselin; Manuel Jorge Cardoso (UNSURE/GRAIL@MICCAI, 2020)

Test-Time Unsupervised Domain Adaptation. - Thomas Varsavsky; Mauricio Orbes-Arteaga; Carole H. Sudre; Mark S. Graham; Parashkev Nachev; M. Jorge Cardoso (MICCAI (1), 2020)

Learning to Segment When Experts Disagree. - Le Zhang 005; Ryutaro Tanno; Kevin Bronik; Chen Jin; Parashkev Nachev; Frederik Barkhof; Olga Ciccarelli; Daniel C. Alexander (MICCAI (1), 2020)

Neuromorphologicaly-preserving Volumetric data encoding using VQ-VAE. - Petru-Daniel Tudosiu; Thomas Varsavsky; Richard Shaw; Mark S. Graham; Parashkev Nachev; Sébastien Ourselin; Carole H. Sudre; M. Jorge Cardoso (CoRR, 2020)

Generative Model-Enhanced Human Motion Prediction. - Anthony Bourached; Ryan-Rhys Griffiths; Robert J. Gray; Ashwani Jha; Parashkev Nachev (CoRR, 2020)

Full-waveform inversion imaging of the human brain. - Lluís Guasch; Oscar Calderon Agudo; Meng-Xing Tang; Parashkev Nachev; Michael Warner (npj Digit. Medicine, 2020)

An MRF-UNet Product of Experts for Image Segmentation. - Mikael Brudfors; Yaël Balbastre; John Ashburner; Geraint Rees 001; Parashkev Nachev; Sébastien Ourselin; M. Jorge Cardoso (MIDL, 2021)

Unsupervised Brain Anomaly Detection and Segmentation with Transformers. - Walter Hugo Lopez Pinaya; Petru-Daniel Tudosiu; Robert J. Gray; Geraint Rees 001; Parashkev Nachev; Sébastien Ourselin; M. Jorge Cardoso (MIDL, 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)

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)

How Can Spherical CNNs Benefit ML-Based Diffusion MRI Parameter Estimation? - Tobias Goodwin-Allcock; Jason D. McEwen; Robert J. Gray; Parashkev Nachev; Hui Zhang 005 (CDMRI@MICCAI, 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 001; Yee-Haur Mah; Andrew D. MacKinnon; James T. Teo; Hans Rolf Jäger; David Werring; Geraint Rees 001; et al. (MICCAI (8), 2022)

Brain Imaging Generation with Latent Diffusion Models. - Walter H. L. Pinaya; Petru-Daniel Tudosiu; Jessica Dafflon; Pedro F. Da Costa; Virginia Fernandez; Parashkev Nachev; Sébastien Ourselin; M. Jorge Cardoso (DGM4MICCAI@MICCAI, 2022)

Morphology-Preserving Autoregressive 3D Generative Modelling of the Brain. - Petru-Daniel Tudosiu; Walter Hugo Lopez Pinaya; Mark S. Graham; Pedro Borges; Virginia Fernandez; Dai Yang; Jeremy Appleyard; Guido Novati; Disha Mehra; Mike Vella; Parashkev Nachev; Sébastien Ourselin; et al. (SASHIMI@MICCAI, 2022)

Transformer-based out-of-distribution detection for clinically safe segmentation. - Mark S. Graham; Petru-Daniel Tudosiu; Paul Wright 001; Walter Hugo Lopez Pinaya; Jean-Marie U.-King-Im; Yee-Haur Mah; James T. Teo; Hans Rolf Jäger; David Werring; Parashkev Nachev; Sébastien Ourselin; M. Jorge Cardoso (MIDL, 2022)

Fitting Segmentation Networks on Varying Image Resolutions Using Splatting. - Mikael Brudfors; Yaël Balbastre; John Ashburner; Geraint Rees 001; Parashkev Nachev; Sébastien Ourselin; M. Jorge Cardoso (MIUA, 2022)

Solid NURBS Conforming Scaffolding for Isogeometric Analysis. - Stefano Moriconi; Parashkev Nachev; Sébastien Ourselin; M. Jorge Cardoso (CoRR, 2022)

Translating automated brain tumour phenotyping to clinical neuroimaging. - James K. Ruffle; Samia Mohinta; Robert J. Gray; Harpreet Hyare; Parashkev Nachev (CoRR, 2022)

Unsupervised brain imaging 3D anomaly detection and segmentation with transformers. - Walter H. L. Pinaya; Petru-Daniel Tudosiu; Robert J. Gray; Geraint Rees 001; Parashkev Nachev; Sébastien Ourselin; M. Jorge Cardoso (Medical Image Anal., 2022)

Representational ethical model calibration. - Robert Carruthers; Isabel Straw; James K. Ruffle; Daniel Herron; Amy P. K. Nelson; Danilo Bzdok; Delmiro Fernandez-Reyes; Geraint Rees 001; Parashkev Nachev (npj Digit. Medicine, 2022)

GeoSPM: Geostatistical parametric mapping for medicine. - Holger Engleitner; Ashwani Jha; Marta Suárez-Pinilla; Amy P. K. Nelson; Daniel Herron; Geraint Rees 001; Karl J. Friston; Martin Rossor; Parashkev Nachev (Patterns, 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; et al. (Patterns, 2022)

3d_very_deep_vae. - Robert J. Gray; Matthew Graham; M. Jorge Cardoso; Sébastien Ourselin; Geraint Rees 001; Parashkev Nachev (Zenodo, 2022)

Framework to Generate Perfusion Map from CT and CTA Images in Patients with Acute Ischemic Stroke: A Longitudinal and Cross-Sectional Study. - Chayanin Tangwiriyasakul; Pedro Borges; Stefano Moriconi; Paul Wright 001; Yee-Haur Mah; James T. Teo; Parashkev Nachev; Sébastien Ourselin; M. Jorge Cardoso (BrainLes/SWITCH@MICCAI, 2023)

Denoising diffusion models for out-of-distribution detection. - Mark S. Graham; Walter H. L. Pinaya; Petru-Daniel Tudosiu; Parashkev Nachev; Sébastien Ourselin; M. Jorge Cardoso (CVPR Workshops, 2023)

Unsupervised Heteromodal Physics-Informed Representation of MRI Data: Tackling Data Harmonisation, Imputation and Domain Shift. - Pedro Borges; Virginia Fernandez; Petru-Daniel Tudosiu; Parashkev Nachev; Sébastien Ourselin; M. Jorge Cardoso (SASHIMI@MICCAI, 2023)

Unsupervised 3D Out-of-Distribution Detection with Latent Diffusion Models. - Mark S. Graham; Walter Hugo Lopez Pinaya; Paul Wright 001; Petru-Daniel Tudosiu; Yee-Haur Mah; James T. Teo; Hans Rolf Jäger; David Werring; Parashkev Nachev; Sébastien Ourselin; M. Jorge Cardoso (MICCAI (1), 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 001; Ashwani Jha; Parashkev Nachev (ML4MHD, 2023)

Deep Variational Lesion-Deficit Mapping. - Guilherme Pombo; Robert J. Gray; Amy P. K. Nelson; Chris Foulon; John Ashburner; 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)

Generative AI for Medical Imaging: extending the MONAI Framework. - Walter H. L. Pinaya; Mark S. Graham; Eric Kerfoot; Petru-Daniel Tudosiu; Jessica Dafflon; Virginia Fernandez; Pedro Sanchez; Julia Wolleb; Pedro F. Da Costa; Ashay Patel; Hyungjin Chung; Can Zhao 001; et al. (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)

The legibility of the imaged human brain. - James K. Ruffle; Robert J. Gray; Samia Mohinta; Guilherme Pombo; Chaitanya Kaul; Harpreet Hyare; Geraint Rees 001; Parashkev Nachev (CoRR, 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)

RAISE - Radiology AI Safety, an End-to-end lifecycle approach. - M. Jorge Cardoso; Julia Moosbauer; Tessa Sundaram Cook; Barbaros Selnur Erdal; Brad W. Genereaux; Vikash Gupta; Bennett A. Landman; Tiarna Lee; Parashkev Nachev; Elanchezhian Somasundaram; Ronald M. Summers; Khaled Younis; et al. (CoRR, 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 001; John Ashburner; Parashkev Nachev (Medical Image Anal., 2023)

Prediction of Stroke Onset Time With Combined Fast High-Resolution Magnetic Resonance Spectroscopic and Quantitative T2 Mapping. - Ziyu Meng; Rong Guo; Tianyao Wang; Bin Bo; Zengping Lin; Yudu Li; Yibo Zhao 004; Xin Yu; David J. Lin; Parashkev Nachev; Zhi-Pei Liang; Yao Li 010 (IEEE Trans. Biomed. Eng., 2023)

Latent Transformer Models for out-of-distribution detection. - Mark S. Graham; Petru-Daniel Tudosiu; Paul Wright 001; Walter Hugo Lopez Pinaya; Petteri Teikari; Ashay Patel; Jean-Marie U.-King-Im; Yee-Haur Mah; James T. Teo; Hans Rolf Jäger; David Werring; Geraint Rees 001; et al. (Medical Image Anal., 2023)

Using MR Physics for Domain Generalisation and Super-Resolution. - Pedro Borges; Virginia Fernandez; Petru-Daniel Tudosiu; Parashkev Nachev; Sébastien Ourselin; M. Jorge Cardoso (SASHIMI@MICCAI, 2024)

VASARI-auto: equitable, efficient, and economical featurisation of glioma MRI. - James K. Ruffle; Samia Mohinta; Kelly Pegoretti Baruteau; Rebekah Rajiah; Faith Lee; Sebastian Brandner; Parashkev Nachev; Harpreet Hyare (CoRR, 2024)

Deep Generative Classification of Blood Cell Morphology. - Simon Deltadahl; Julian D. Gilbey; Christine van Laer; Nancy Boeckx; Mathie P. G. Leers; Tanya Freeman; Laura Aiken; Timothy Farren; Matthew Smith; Mohamad Zeina; BloodCounts Consortium; Concetta Piazzese; et al. (CoRR, 2024)

UniBrain: A Unified Model for Cross-Subject Brain Decoding. - Zicheng Wang; Zhen Zhao; Luping Zhou; Parashkev Nachev (CoRR, 2024)

Realistic morphology-preserving generative modelling of the brain. - Petru-Daniel Tudosiu; Walter H. L. Pinaya; Pedro Ferreira Da Costa; Jessica Dafflon; Ashay Patel; Pedro Borges; Virginia Fernandez; Mark S. Graham; Robert J. Gray; Parashkev Nachev; Sébastien Ourselin; M. Jorge Cardoso (Nat. Mac. Intell., 2024)

Computational limits to the legibility of the imaged human brain. - James K. Ruffle; Robert J. Gray; Samia Mohinta; Guilherme Pombo; Chaitanya Kaul; Harpreet Hyare; Geraint Rees 001; Parashkev Nachev (NeuroImage, 2024)

Recent methodological advances in federated learning for healthcare. - Fan Zhang; Daniel Kreuter; Yichen Chen; Sören Dittmer; Samuel Tull; Tolou Shadbahr; Martijn Schut; Folkert W. Asselbergs; Sujoy Kar; Suthesh Sivapalaratnam; Sophie Williams; Mickey Koh; et al. (Patterns, 2024)

Neuradicon: Operational representation learning of neuroimaging reports. - Henry C. Watkins; Robert J. Gray; Adam Julius; Yee-Haur Mah; James T. Teo; Walter H. L. Pinaya; Paul Wright 001; Ashwani Jha; Holger Engleitner; Jorge Cardoso 002; Sébastien Ourselin; Geraint Rees 001; et al. (Comput. Methods Programs Biomed., 2025)

Deep generative computed perfusion-deficit mapping of ischaemic stroke. - Chayanin Tangwiriyasakul; Pedro Borges; Guilherme Pombo; Stefano Moriconi; Michael S. Elmalem; Paul Wright 001; Yee-Haur Mah; Jane Rondina; Robert J. Gray; Sébastien Ourselin; Parashkev Nachev; M. Jorge Cardoso (CoRR, 2025)

Generalizable automated ischaemic stroke lesion segmentation with vision transformers. - Chris Foulon; Robert J. Gray; James K. Ruffle; Jonathan Best; Tianbo Xu; Henry C. Watkins; Jane Rondina; Guilherme Pombo; Dominic Giles; Paul Wright 001; Marcela Ovando Tellez; Hans Rolf Jäger; et al. (CoRR, 2025)