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)

ICAM: Interpretable Classification via Disentangled Representations and Feature Attribution Mapping. - Cher Bass; Mariana da Silva; Carole H. Sudre; Petru-Daniel Tudosiu; Stephen M. Smith 001; Emma C. Robinson (NeurIPS, 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)

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)

ICAM-reg: Interpretable Classification and Regression with Feature Attribution for Mapping Neurological Phenotypes in Individual Scans. - Cher Bass; Mariana da Silva; Carole H. Sudre; Logan Z. J. Williams; Petru-Daniel Tudosiu; Fidel Alfaro-Almagro; Sean P. Fitzgibbon; Matthew F. Glasser; Stephen M. Smith 001; Emma C. Robinson (CoRR, 2021)

Can Segmentation Models Be Trained with Fully Synthetically Generated Data? - Virginia Fernandez; Walter Hugo Lopez Pinaya; Pedro Borges; Petru-Daniel Tudosiu; Mark S. Graham; Tom Vercauteren; M. Jorge Cardoso (SASHIMI@MICCAI, 2022)

Cross Attention Transformers for Multi-modal Unsupervised Whole-Body PET Anomaly Detection. - Ashay Patel; Petru-Daniel Tudosiu; Walter Hugo Lopez Pinaya; Gary J. Cook; Vicky Goh; Sébastien Ourselin; M. Jorge Cardoso (DGM4MICCAI@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)

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)

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)

Self-Supervised Anomaly Detection from Anomalous Training Data via Iterative Latent Token Masking. - Ashay Patel; Petru-Daniel Tudosiu; Walter H. L. Pinaya; Mark S. Graham; Olusola Adeleke; Gary J. Cook; Vicky Goh; Sébastien Ourselin; M. Jorge Cardoso (ICCV (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)

Geometry-Invariant Abnormality Detection. - Ashay Patel; Petru-Daniel Tudosiu; Walter Hugo Lopez Pinaya; Olusola Adeleke; Gary J. Cook; Vicky Goh; Sébastien Ourselin; M. Jorge Cardoso (MICCAI (1), 2023)

InverseSR: 3D Brain MRI Super-Resolution Using a Latent Diffusion Model. - Jueqi Wang; Jacob Levman; Walter Hugo Lopez Pinaya; Petru-Daniel Tudosiu; M. Jorge Cardoso; Razvan V. Marinescu (MICCAI (10), 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)

Optimisation-Based Multi-Modal Semantic Image Editing. - Bowen Li; Yongxin Yang; Steven McDonagh 001; Shifeng Zhang; Petru-Daniel Tudosiu; Sarah Parisot (CoRR, 2023)

ICAM-Reg: Interpretable Classification and Regression With Feature Attribution for Mapping Neurological Phenotypes in Individual Scans. - Cher Bass; Mariana da Silva; Carole H. Sudre; Logan Z. J. Williams; Helena S. Sousa; Petru-Daniel Tudosiu; Fidel Alfaro-Almagro; Sean P. Fitzgibbon; Matthew F. Glasser; Stephen M. Smith 001; Emma C. Robinson (IEEE Trans. Medical Imaging, 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)

MULAN: A Multi Layer Annotated Dataset for Controllable Text-to-Image Generation. - Petru-Daniel Tudosiu; Yongxin Yang; Shifeng Zhang; Fei Chen; Steven McDonagh 001; Gerasimos Lampouras; Ignacio Iacobacci; Sarah Parisot (CVPR, 2024)

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)

Generating compositional scenes via Text-to-image RGBA Instance Generation. - Alessandro Fontanella; Petru-Daniel Tudosiu; Yongxin Yang; Shifeng Zhang; Sarah Parisot (NeurIPS, 2024)

Generating multi-pathological and multi-modal images and labels for brain MRI. - Virginia Fernandez; Walter Hugo Lopez Pinaya; Pedro Borges; Mark S. Graham; Petru-Daniel Tudosiu; Tom Vercauteren; M. Jorge Cardoso (Medical Image Anal., 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)

Exploiting Mixture-of-Experts Redundancy Unlocks Multimodal Generative Abilities. - Raman Dutt; Harleen Hanspal; Guoxuan Xia; Petru-Daniel Tudosiu; Alexander Black 001; Yongxin Yang; Steven McDonagh 001; Sarah Parisot (CoRR, 2025)

A Practical Investigation of Spatially-Controlled Image Generation with Transformers. - Guoxuan Xia; Harleen Hanspal; Petru-Daniel Tudosiu; Shifeng Zhang; Sarah Parisot (CoRR, 2025)