Mikael Brudfors

Publication Activity (10 Years)

Years Active: 2015-2023
Publications (10 Years): 30

Top Topics

Image Registration

Total Variation

Blind Deconvolution

Top Venues

Medical Image Anal.

Publications

Liam F. Chalcroft, Ruben Lourenço Pereira, Mikael Brudfors, Andrew S. Kayser, Mark D'Esposito, Cathy J. Price, Ioannis Pappas, John Ashburner
Large-kernel Attention for Efficient and Robust Brain Lesion Segmentation. CoRR (2023)
Alessa Hering, Lasse Hansen, Tony C. W. Mok, Albert C. S. Chung, Hanna Siebert, Stephanie Häger, Annkristin Lange, Sven Kuckertz, Stefan Heldmann, Wei Shao, Sulaiman Vesal, Mirabela Rusu, Geoffrey A. Sonn, Théo Estienne, Maria Vakalopoulou, Luyi Han, Yunzhi Huang, Pew-Thian Yap, Mikael Brudfors, Yaël Balbastre, Samuel Joutard, Marc Modat, Gal Lifshitz, Dan Raviv, Jinxin Lv, Qiang Li, Vincent Jaouen, Dimitris Visvikis, Constance Fourcade, Mathieu Rubeaux, Wentao Pan, Zhe Xu, Bailiang Jian, Francesca De Benetti, Marek Wodzinski, Niklas Gunnarsson, Jens Sjölund, Daniel Grzech, Huaqi Qiu, Zeju Li, Alexander Thorley, Jinming Duan, Christoph Großbröhmer, Andrew Hoopes, Ingerid Reinertsen, Yiming Xiao, Bennett A. Landman, Yuankai Huo, Keelin Murphy, Nikolas Lessmann, Bram van Ginneken, Adrian V. Dalca, Mattias P. Heinrich
Learn2Reg: Comprehensive Multi-Task Medical Image Registration Challenge, Dataset and Evaluation in the Era of Deep Learning. IEEE Trans. Medical Imaging 42 (3) (2023)
Mikael Brudfors, Yaël Balbastre, John Ashburner, Geraint Rees, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso
Fitting Segmentation Networks on Varying Image Resolutions Using Splatting. MIUA (2022)
Mikael Brudfors, Yaël Balbastre, John Ashburner, Geraint Rees, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso
Fitting Segmentation Networks on Varying Image Resolutions using Splatting. CoRR (2022)
Mikael Brudfors, Yaël Balbastre, John Ashburner, Geraint Rees, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso
An MRF-UNet Product of Experts for Image Segmentation. CoRR (2021)
Yaël Balbastre, Mikael Brudfors, Michela Azzarito, Christian Lambert, Martina F. Callaghan, John Ashburner
Model-based multi-parameter mapping. Medical Image Anal. 73 (2021)
Yaël Balbastre, Ali Aghaeifar, Nadège Corbin, Mikael Brudfors, John Ashburner, Martina F. Callaghan
Correcting inter-scan motion artefacts in quantitative R1 mapping at 7T. CoRR (2021)
Yaël Balbastre, Mikael Brudfors, Michela Azzarito, Christian Lambert, Martina F. Callaghan, John Ashburner
Model-based multi-parameter mapping. CoRR (2021)
Yu Yan, Yaël Balbastre, Mikael Brudfors, John Ashburner
Factorisation-based Image Labelling. CoRR (2021)
Mikael Brudfors, Yaël Balbastre, John Ashburner, Geraint Rees, Parashkev Nachev, Sébastien Ourselin, M. Jorge Cardoso
An MRF-UNet Product of Experts for Image Segmentation. MIDL (2021)
Alessa Hering, Lasse Hansen, Tony C. W. Mok, Albert C. S. Chung, Hanna Siebert, Stephanie Häger, Annkristin Lange, Sven Kuckertz, Stefan Heldmann, Wei Shao, Sulaiman Vesal, Mirabela Rusu, Geoffrey A. Sonn, Théo Estienne, Maria Vakalopoulou, Luyi Han, Yunzhi Huang, Mikael Brudfors, Yaël Balbastre, Samuel Joutard, Marc Modat, Gal Lifshitz, Dan Raviv, Jinxin Lv, Qiang Li, Vincent Jaouen, Dimitris Visvikis, Constance Fourcade, Mathieu Rubeaux, Wentao Pan, Zhe Xu, Bailiang Jian, Francesca De Benetti, Marek Wodzinski, Niklas Gunnarsson, Huaqi Qiu, Zeju Li, Christoph Großbröhmer, Andrew Hoopes, Ingerid Reinertsen, Yiming Xiao, Bennett A. Landman, Yuankai Huo, Keelin Murphy, Bram van Ginneken, Adrian V. Dalca, Mattias P. Heinrich
Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning. CoRR (2021)
Yaël Balbastre, Mikael Brudfors, Michela Azzarito, Christian Lambert, Martina F. Callaghan, John Ashburner
Joint Total Variation ESTATICS for Robust Multi-parameter Mapping. MICCAI (2) (2020)
Mikael Brudfors, Yaël Balbastre, Guillaume Flandin, Parashkev Nachev, John Ashburner
Flexible Bayesian Modelling for Nonlinear Image Registration. MICCAI (3) (2020)
Mikael Brudfors, Yaël Balbastre, Guillaume Flandin, Parashkev Nachev, John Ashburner
Flexible Bayesian Modelling for Nonlinear Image Registration. CoRR (2020)
Yaël Balbastre, Mikael Brudfors, Michela Azzarito, Christian Lambert, Martina F. Callaghan, John Ashburner
Joint Total Variation ESTATICS for Robust Multi-Parameter Mapping. CoRR (2020)
Mikael Brudfors, Yaël Balbastre, John Ashburner
Groupwise Multimodal Image Registration using Joint Total Variation. CoRR (2020)
Mikael Brudfors, Yaël Balbastre, John Ashburner
Groupwise Multimodal Image Registration Using Joint Total Variation. MIUA (2020)
Mikael Brudfors, John Ashburner, Parashkev Nachev, Yaël Balbastre
Empirical Bayesian Mixture Models for Medical Image Translation. CoRR (2019)
John Ashburner, Mikael Brudfors, Kevin Bronik, Yaël Balbastre
An algorithm for learning shape and appearance models without annotations. Medical Image Anal. 55 (2019)
Neil P. Oxtoby, Fabio S. Ferreira, Ágoston Mihalik, Tong Wu, Mikael Brudfors, Hongxiang Lin, Anita Rau, Stefano B. Blumberg, Maria Robu, Cemre Zor, Maira Tariq, Mar Estarellas Garcia, Baris Kanber, Daniil I. Nikitichev, Janaina Mourão Miranda
ABCD Neurocognitive Prediction Challenge 2019: Predicting Individual Residual Fluid Intelligence Scores from Cortical Grey Matter Morphology. ABCD-NP@MICCAI (2019)
Ágoston Mihalik, Mikael Brudfors, Maria Robu, Fabio S. Ferreira, Hongxiang Lin, Anita Rau, Tong Wu, Stefano B. Blumberg, Baris Kanber, Maira Tariq, Mar Estarellas Garcia, Cemre Zor, Daniil I. Nikitichev, Janaina Mourão Miranda, Neil P. Oxtoby
ABCD Neurocognitive Prediction Challenge 2019: Predicting Individual Fluid Intelligence Scores from Structural MRI Using Probabilistic Segmentation and Kernel Ridge Regression. ABCD-NP@MICCAI (2019)
Mikael Brudfors, John Ashburner, Parashkev Nachev, Yaël Balbastre
Empirical Bayesian Mixture Models for Medical Image Translation. SASHIMI@MICCAI (2019)
Mikael Brudfors, Yaël Balbastre, Parashkev Nachev, John Ashburner
A Tool for Super-Resolving Multimodal Clinical MRI. CoRR (2019)
Mikael Brudfors, Yaël Balbastre, John Ashburner
Nonlinear Markov Random Fields Learned via Backpropagation. CoRR (2019)
Mikael Brudfors, Yaël Balbastre, John Ashburner
Nonlinear Markov Random Fields Learned via Backpropagation. IPMI (2019)
Yaël Balbastre, Mikael Brudfors, Kevin Bronik, John Ashburner
Diffeomorphic Brain Shape Modelling Using Gauss-Newton Optimisation. MICCAI (1) (2018)
Mikael Brudfors, Yaël Balbastre, Parashkev Nachev, John Ashburner
MRI Super-Resolution Using Multi-channel Total Variation. MIUA (2018)
Yaël Balbastre, Mikael Brudfors, Kevin Bronik, John Ashburner
Diffeomorphic brain shape modelling using Gauss-Newton optimisation. CoRR (2018)
John Ashburner, Mikael Brudfors, Kevin Bronik, Yaël Balbastre
An Algorithm for Learning Shape and Appearance Models without Annotations. CoRR (2018)
Mikael Brudfors, Yaël Balbastre, Parashkev Nachev, John Ashburner
MRI Super-Resolution using Multi-Channel Total Variation. CoRR (2018)
Mikael Brudfors, Alexander Seitel, Abtin Rasoulian, Andras Lasso, Victoria A. Lessoway, Jill Osborn, Atsuto Maki, Robert N. Rohling, Purang Abolmaesumi
Towards real-time, tracker-less 3D ultrasound guidance for spine anaesthesia. Int. J. Comput. Assist. Radiol. Surg. 10 (6) (2015)