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Mark S. Graham
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2020 – today
- 2024
- [j7]Virginia Fernandez, Walter Hugo Lopez Pinaya, Pedro Borges, Mark S. Graham, Petru-Daniel Tudosiu, Tom Vercauteren, M. Jorge Cardoso:
Generating multi-pathological and multi-modal images and labels for brain MRI. Medical Image Anal. 97: 103278 (2024) - 2023
- [j6]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:
Latent Transformer Models for out-of-distribution detection. Medical Image Anal. 90: 102967 (2023) - [c12]Mark S. Graham, Walter H. L. Pinaya, Petru-Daniel Tudosiu, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Denoising diffusion models for out-of-distribution detection. CVPR Workshops 2023: 2948-2957 - [c11]Ashay Patel, Petru-Daniel Tudosiu, Walter H. L. Pinaya, Mark S. Graham, Olusola Adeleke, Gary J. Cook, Vicky Goh, Sébastien Ourselin, M. Jorge Cardoso:
Self-Supervised Anomaly Detection from Anomalous Training Data via Iterative Latent Token Masking. ICCV (Workshops) 2023: 2394-2402 - [c10]Virginia Fernandez, Walter Hugo Lopez Pinaya, Pedro Borges, Mark S. Graham, Tom Vercauteren, M. Jorge Cardoso:
A 3D Generative Model of Pathological Multi-modal MR Images and Segmentations. DGM4MICCAI 2023: 132-142 - [c9]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:
Unsupervised 3D Out-of-Distribution Detection with Latent Diffusion Models. MICCAI (1) 2023: 446-456 - [i13]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:
Unsupervised 3D out-of-distribution detection with latent diffusion models. CoRR abs/2307.03777 (2023) - [i12]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:
Generative AI for Medical Imaging: extending the MONAI Framework. CoRR abs/2307.15208 (2023) - [i11]Virginia Fernandez, Walter Hugo Lopez Pinaya, Pedro Borges, Mark S. Graham, Tom Vercauteren, M. Jorge Cardoso:
A 3D generative model of pathological multi-modal MR images and segmentations. CoRR abs/2311.04552 (2023) - 2022
- [c8]Antoine Legouhy, Mark S. Graham, Michele Guerreri, Whitney Stee, Thomas Villemonteix, Philippe Peigneux, Hui Zhang:
Correction of Susceptibility Distortion in EPI: A Semi-supervised Approach with Deep Learning. CDMRI@MICCAI 2022: 38-49 - [c7]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:
Morphology-Preserving Autoregressive 3D Generative Modelling of the Brain. SASHIMI@MICCAI 2022: 66-78 - [c6]Virginia Fernandez, Walter Hugo Lopez Pinaya, Pedro Borges, Petru-Daniel Tudosiu, Mark S. Graham, Tom Vercauteren, M. Jorge Cardoso:
Can Segmentation Models Be Trained with Fully Synthetically Generated Data? SASHIMI@MICCAI 2022: 79-90 - [c5]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:
Fast Unsupervised Brain Anomaly Detection and Segmentation with Diffusion Models. MICCAI (8) 2022: 705-714 - [c4]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:
Transformer-based out-of-distribution detection for clinically safe segmentation. MIDL 2022: 457-476 - [i10]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:
Transformer-based out-of-distribution detection for clinically safe segmentation. CoRR abs/2205.10650 (2022) - [i9]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:
Fast Unsupervised Brain Anomaly Detection and Segmentation with Diffusion Models. CoRR abs/2206.03461 (2022) - [i8]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, Jorge Cardoso:
Morphology-preserving Autoregressive 3D Generative Modelling of the Brain. CoRR abs/2209.03177 (2022) - [i7]Virginia Fernandez, Walter Hugo Lopez Pinaya, Pedro Borges, Petru-Daniel Tudosiu, Mark S. Graham, Tom Vercauteren, M. Jorge Cardoso:
Can segmentation models be trained with fully synthetically generated data? CoRR abs/2209.08256 (2022) - [i6]Mark S. Graham, Walter H. L. Pinaya, Petru-Daniel Tudosiu, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Denoising Diffusion Models for Out-of-Distribution Detection. CoRR abs/2211.07740 (2022) - 2020
- [c3]Mark S. Graham, Carole H. Sudre, Thomas Varsavsky, Petru-Daniel Tudosiu, Parashkev Nachev, Sébastien Ourselin, Manuel Jorge Cardoso:
Hierarchical Brain Parcellation with Uncertainty. UNSURE/GRAIL@MICCAI 2020: 23-31 - [c2]Thomas Varsavsky, Mauricio Orbes-Arteaga, Carole H. Sudre, Mark S. Graham, Parashkev Nachev, M. Jorge Cardoso:
Test-Time Unsupervised Domain Adaptation. MICCAI (1) 2020: 428-436 - [i5]Petru-Daniel Tudosiu, Thomas Varsavsky, Richard Shaw, Mark S. Graham, Parashkev Nachev, Sébastien Ourselin, Carole H. Sudre, M. Jorge Cardoso:
Neuromorphologicaly-preserving Volumetric data encoding using VQ-VAE. CoRR abs/2002.05692 (2020) - [i4]Mark S. Graham, Carole H. Sudre, Thomas Varsavsky, Petru-Daniel Tudosiu, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso:
Hierarchical brain parcellation with uncertainty. CoRR abs/2009.07573 (2020) - [i3]Thomas Varsavsky, Mauricio Orbes-Arteaga, Carole H. Sudre, Mark S. Graham, Parashkev Nachev, M. Jorge Cardoso:
Test-time Unsupervised Domain Adaptation. CoRR abs/2010.01926 (2020) - [i2]Benjamin Murray, Eric Kerfoot, Mark S. Graham, Carole H. Sudre, Erika Molteni, Liane S. Canas, Michela Antonelli, Alessia Visconti, Andrew T. Chan, Paul W. Franks, Richard Davies, Jonathan Wolf, Tim D. Spector, Claire J. Steves, Marc Modat, Sébastien Ourselin:
Accessible Data Curation and Analytics for International-Scale Citizen Science Datasets. CoRR abs/2011.00867 (2020)
2010 – 2019
- 2019
- [i1]Kanwal K. Bhatia, Mark S. Graham, Louise Terry, Ashley Wood, Paris Tranos, Sameer Trikha, Nicolas Jaccard:
Disease classification of macular Optical Coherence Tomography scans using deep learning software: validation on independent, multi-centre data. CoRR abs/1907.05164 (2019) - 2018
- [j5]Jesper L. R. Andersson, Mark S. Graham, Ivana Drobnjak, Hui Zhang, Jon Campbell:
Susceptibility-induced distortion that varies due to motion: Correction in diffusion MR without acquiring additional data. NeuroImage 171: 277-295 (2018) - [j4]Mark S. Graham, Ivana Drobnjak, Hui Zhang:
A supervised learning approach for diffusion MRI quality control with minimal training data. NeuroImage 178: 668-676 (2018) - 2017
- [j3]Jesper L. R. Andersson, Mark S. Graham, Ivana Drobnjak, Hui Zhang, Nicola Filippini, Matteo Bastiani:
Towards a comprehensive framework for movement and distortion correction of diffusion MR images: Within volume movement. NeuroImage 152: 450-466 (2017) - 2016
- [j2]Mark S. Graham, Ivana Drobnjak, Hui Zhang:
Realistic simulation of artefacts in diffusion MRI for validating post-processing correction techniques. NeuroImage 125: 1079-1094 (2016) - [j1]Jesper L. R. Andersson, Mark S. Graham, Eniko Zsoldos, Stamatios N. Sotiropoulos:
Incorporating outlier detection and replacement into a non-parametric framework for movement and distortion correction of diffusion MR images. NeuroImage 141: 556-572 (2016) - 2015
- [c1]Mark S. Graham, Ivana Drobnjak, Hui Zhang:
A Simulation Framework for Quantitative Validation of Artefact Correction in Diffusion MRI. IPMI 2015: 638-649
Coauthor Index
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