Petru-Daniel Tudosiu

According to our database, Petru-Daniel Tudosiu authored at least 22 papers between 2020 and 2023.

Collaborative distances:

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

2023

Latent Transformer Models for out-of-distribution detection.

Mark S. Graham, Petru-Daniel Tudosiu, Paul Wright, Walter Hugo Lopez Pinaya, Petteri Teikari, Ashay Patel, Jean-Marie U.-King-Im, Yee H. Mah, James T. Teo, Hans Rolf Jäger, David Werring, Geraint Rees, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso

Medical Image Anal., December, 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, Emma C. Robinson

IEEE Trans. Medical Imaging, April, 2023

Optimisation-Based Multi-Modal Semantic Image Editing.

Bowen Li, Yongxin Yang, Steven McDonagh, Shifeng Zhang, Petru-Daniel Tudosiu, Sarah Parisot

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, Wei Peng, Zelong Liu, XueYan Mei, Oeslle Lucena, Jong Chul Ye, Sotirios A. Tsaftaris, Prerna Dogra, Andrew Feng, Marc Modat, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso

CoRR, 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

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 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

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Unsupervised 3D Out-of-Distribution Detection with Latent Diffusion Models.

Mark S. Graham, Walter Hugo Lopez Pinaya, Paul Wright, Petru-Daniel Tudosiu, Yee H. Mah, James T. Teo, Hans Rolf Jäger, David Werring, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 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

Proceedings of the Simulation and Synthesis in Medical Imaging, 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

Proceedings of the IEEE/CVF International Conference on Computer Vision, 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

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

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

Transformer-based out-of-distribution detection for clinically safe segmentation.

Mark S. Graham, Petru-Daniel Tudosiu, Paul Wright, Walter Hugo Lopez Pinaya, Jean-Marie U.-King-Im, Yee H. Mah, James T. Teo, Hans Rolf Jäger, David Werring, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso

Proceedings of the International Conference on Medical Imaging with Deep Learning, 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, M. Jorge Cardoso

Proceedings of the Simulation and Synthesis in Medical Imaging, 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

Proceedings of the Deep Generative Models - Second MICCAI Workshop, 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

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

Proceedings of the Deep Generative Models - Second MICCAI Workshop, 2022

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

Proceedings of the Simulation and Synthesis in Medical Imaging, 2022

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, Emma C. Robinson

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

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

ICAM: Interpretable Classification via Disentangled Representations and Feature Attribution Mapping.

Cher Bass, Mariana da Silva, Carole H. Sudre, Petru-Daniel Tudosiu, Stephen M. Smith, Emma C. Robinson

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Hierarchical Brain Parcellation with Uncertainty.

Mark S. Graham, Carole H. Sudre, Thomas Varsavsky, Petru-Daniel Tudosiu, Parashkev Nachev, Sébastien Ourselin, Manuel Jorge Cardoso

Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis, 2020