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Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning.

A. Hering, L. Hansen, T. Mok, A. Chung, H. Siebert, S. Häger, A. Lange, S. Kuckertz, S. Heldmann, W. Shao, S. Vesal, M. Rusu, G. Sonn, T. Estienne, M. Vakalopoulou, L. Han, Y. Huang, M. Brudfors, Y. Balbastre, S. Joutard, M. Modat, G. Lifshitz, D. Raviv, J. Lv, Q. Li, V. Jaouen, D. Visvikis, C. Fourcade, M. Rubeaux, W. Pan, Z. Xu, B. Jian, F. Benetti, M. Wodzinski, N. Gunnarsson, H. Qiu, Z. Li, C. Großbröhmer, A. Hoopes, I. Reinertsen, Y. Xiao, B. Landman, Y. Huo, K. Murphy, B. van Ginneken, A. Dalca, and M. Heinrich. CoRR, (2021)

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Mikael Simons

Mikael Agopov

Mikael Högqvist

Mikael Vaaraniemi

Mikael Berndtsson

Other publications of authors with the same name

Towards real-time, tracker-less 3D ultrasound guidance for spine anaesthesia.M. Brudfors, A. Seitel, A. Rasoulian, A. Lasso, V. Lessoway, J. Osborn, A. Maki, R. Rohling, and P. Abolmaesumi. Int. J. Comput. Assist. Radiol. Surg., 10 (6): 855-865 (2015)ABCD Neurocognitive Prediction Challenge 2019: Predicting Individual Fluid Intelligence Scores from Structural MRI Using Probabilistic Segmentation and Kernel Ridge Regression.Á. Mihalik, M. Brudfors, M. Robu, F. Ferreira, H. Lin, A. Rau, T. Wu, S. Blumberg, B. Kanber, M. Tariq and 5 other author(s). ABCD-NP@MICCAI, volume 11791 of Lecture Notes in Computer Science, page 133-142. Springer, (2019)A Tool for Super-Resolving Multimodal Clinical MRI.M. Brudfors, Y. Balbastre, P. Nachev, and J. Ashburner. CoRR, (2019)Large-kernel Attention for Efficient and Robust Brain Lesion Segmentation.L. Chalcroft, R. Pereira, M. Brudfors, A. Kayser, M. D'Esposito, C. Price, I. Pappas, and J. Ashburner. CoRR, (2023)Correcting inter-scan motion artefacts in quantitative R1 mapping at 7T.Y. Balbastre, A. Aghaeifar, N. Corbin, M. Brudfors, J. Ashburner, and M. Callaghan. CoRR, (2021)Learn2Reg: Comprehensive Multi-Task Medical Image Registration Challenge, Dataset and Evaluation in the Era of Deep Learning.A. Hering, L. Hansen, T. Mok, A. Chung, H. Siebert, S. Häger, A. Lange, S. Kuckertz, S. Heldmann, W. Shao and 43 other author(s). IEEE Trans. Medical Imaging, 42 (3): 697-712 (March 2023)Factorisation-based Image Labelling.Y. Yan, Y. Balbastre, M. Brudfors, and J. Ashburner. CoRR, (2021)An MRF-UNet Product of Experts for Image Segmentation.M. Brudfors, Y. Balbastre, J. Ashburner, G. Rees, P. Nachev, S. Ourselin, and M. Cardoso. MIDL, volume 143 of Proceedings of Machine Learning Research, page 48-59. PMLR, (2021)Nonlinear Markov Random Fields Learned via Backpropagation.M. Brudfors, Y. Balbastre, and J. Ashburner. IPMI, volume 11492 of Lecture Notes in Computer Science, page 805-817. Springer, (2019)Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning.A. Hering, L. Hansen, T. Mok, A. Chung, H. Siebert, S. Häger, A. Lange, S. Kuckertz, S. Heldmann, W. Shao and 37 other author(s). CoRR, (2021)

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Disambiguation of "Brudfors, Mikael"

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Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning.

Please choose a person to relate this publication to

Mikael Simons

Mikael Agopov

Mikael Högqvist

Mikael Vaaraniemi

Mikael Berndtsson

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Brudfors, Mikael"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning.

Please choose a person to relate this publication to

Mikael Simons

Mikael Agopov

Mikael Högqvist

Mikael Vaaraniemi

Mikael Berndtsson

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
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Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning.