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ORCIDMikael Brudfors
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2020 – today
- 2024
[c12]Mikael Brudfors, Mark Graham, Hyungon Ryu, Oliver Kutter:
Monai for Deep-Learning Based CBCT Reconstruction. ICASSP Workshops 2024: 75-76- [i17]Adrito Das, Bilal Sidiqi, Laurent Mennillo, Zhehua Mao, Mikael Brudfors, Miguel Xochicale, Danyal Z. Khan, Nicola Newall, John G. Hanrahan, Matthew J. Clarkson, Danail Stoyanov, Hani J. Marcus, Sophia Bano:
Automated Surgical Skill Assessment in Endoscopic Pituitary Surgery using Real-time Instrument Tracking on a High-fidelity Bench-top Phantom. CoRR abs/2409.17025 (2024) - 2023
- [j4]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): 697-712 (2023) - [i16]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 abs/2308.07251 (2023) - 2022
- [c11]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: 271-282 - [i15]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 abs/2206.06445 (2022) - 2021
- [j3]Yaël Balbastre, Mikael Brudfors, Michela Azzarito, Christian Lambert, Martina F. Callaghan, John Ashburner:
Model-based multi-parameter mapping. Medical Image Anal. 73: 102149 (2021) - [c10]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: 48-59 - [i14]Yaël Balbastre, Mikael Brudfors, Michela Azzarito, Christian Lambert, Martina F. Callaghan, John Ashburner:
Model-based multi-parameter mapping. CoRR abs/2102.01604 (2021) - [i13]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 abs/2104.05495 (2021) - [i12]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 abs/2108.10943 (2021) - [i11]Yu Yan, Yaël Balbastre, Mikael Brudfors, John Ashburner:
Factorisation-based Image Labelling. CoRR abs/2111.10326 (2021) - [i10]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 abs/2112.04489 (2021) - 2020
- [c9]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: 53-63 - [c8]Mikael Brudfors, Yaël Balbastre, Guillaume Flandin, Parashkev Nachev, John Ashburner:
Flexible Bayesian Modelling for Nonlinear Image Registration. MICCAI (3) 2020: 253-263 - [c7]Mikael Brudfors, Yaël Balbastre, John Ashburner:
Groupwise Multimodal Image Registration Using Joint Total Variation. MIUA 2020: 184-194 - [i9]Mikael Brudfors, Yaël Balbastre, John Ashburner:
Groupwise Multimodal Image Registration using Joint Total Variation. CoRR abs/2005.02933 (2020) - [i8]Yaël Balbastre, Mikael Brudfors, Michela Azzarito, Christian Lambert, Martina F. Callaghan, John Ashburner:
Joint Total Variation ESTATICS for Robust Multi-Parameter Mapping. CoRR abs/2005.14247 (2020) - [i7]Mikael Brudfors, Yaël Balbastre, Guillaume Flandin, Parashkev Nachev, John Ashburner:
Flexible Bayesian Modelling for Nonlinear Image Registration. CoRR abs/2006.02338 (2020)
2010 – 2019
- 2019
- [j2]John Ashburner, Mikael Brudfors, Kevin Bronik, Yaël Balbastre:
An algorithm for learning shape and appearance models without annotations. Medical Image Anal. 55: 197-215 (2019) - [c6]Mikael Brudfors, Yaël Balbastre, John Ashburner:
Nonlinear Markov Random Fields Learned via Backpropagation. IPMI 2019: 805-817 - [c5]Mikael Brudfors, John Ashburner, Parashkev Nachev, Yaël Balbastre:
Empirical Bayesian Mixture Models for Medical Image Translation. SASHIMI@MICCAI 2019: 1-12 - [c4]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: 114-123 - [c3]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: 133-142 - [i6]Mikael Brudfors, Yaël Balbastre, John Ashburner:
Nonlinear Markov Random Fields Learned via Backpropagation. CoRR abs/1902.10747 (2019) - [i5]Mikael Brudfors, John Ashburner, Parashkev Nachev, Yaël Balbastre:
Empirical Bayesian Mixture Models for Medical Image Translation. CoRR abs/1908.05926 (2019) - [i4]Mikael Brudfors, Yaël Balbastre, Parashkev Nachev, John Ashburner:
A Tool for Super-Resolving Multimodal Clinical MRI. CoRR abs/1909.01140 (2019) - 2018
- [c2]Yaël Balbastre, Mikael Brudfors, Kevin Bronik, John Ashburner:
Diffeomorphic Brain Shape Modelling Using Gauss-Newton Optimisation. MICCAI (1) 2018: 862-870 - [c1]Mikael Brudfors, Yaël Balbastre, Parashkev Nachev, John Ashburner:
MRI Super-Resolution Using Multi-channel Total Variation. MIUA 2018: 217-228 - [i3]Yaël Balbastre, Mikael Brudfors, Kevin Bronik, John Ashburner:
Diffeomorphic brain shape modelling using Gauss-Newton optimisation. CoRR abs/1806.07109 (2018) - [i2]John Ashburner, Mikael Brudfors, Kevin Bronik, Yaël Balbastre:
An Algorithm for Learning Shape and Appearance Models without Annotations. CoRR abs/1807.10731 (2018) - [i1]Mikael Brudfors, Yaël Balbastre, Parashkev Nachev, John Ashburner:
MRI Super-Resolution using Multi-Channel Total Variation. CoRR abs/1810.03422 (2018) - 2015
- [j1]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): 855-865 (2015)
Coauthor Index
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