Maxime Lafarge
Maxime Lafarge
Postdoctoral Researcher, University Hospital Zürich
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Adversarial training and dilated convolutions for brain MRI segmentation
P Moeskops, M Veta, MW Lafarge, KAJ Eppenhof, JPW Pluim
Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical …, 2017
Roto-translation covariant convolutional networks for medical image analysis
EJ Bekkers, MW Lafarge, M Veta, KAJ Eppenhof, JPW Pluim, R Duits
Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018
Domain-adversarial neural networks to address the appearance variability of histopathology images
MW Lafarge, JPW Pluim, KAJ Eppenhof, P Moeskops, M Veta
Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical …, 2017
Deformable image registration using convolutional neural networks
KAJ Eppenhof, MW Lafarge, P Moeskops, M Veta, JPW Pluim
Medical Imaging 2018: Image Processing 10574, 192-197, 2018
Roto-translation equivariant convolutional networks: Application to histopathology image analysis
MW Lafarge, EJ Bekkers, JPW Pluim, R Duits, M Veta
Medical Image Analysis 68, 101849, 2021
Progressively trained convolutional neural networks for deformable image registration
KAJ Eppenhof, MW Lafarge, M Veta, JPW Pluim
IEEE transactions on medical imaging 39 (5), 1594-1604, 2019
Learning domain-invariant representations of histological images
MW Lafarge, JPW Pluim, KAJ Eppenhof, M Veta
Frontiers in medicine 6, 162, 2019
Capturing Single-Cell Phenotypic Variation via Unsupervised Representation Learning
MW Lafarge, JC Caicedo, AE Carpenter, JPW Pluim, S Singh, M Veta
International Conference on Medical Imaging with Deep Learning (MIDL) 102 …, 2018
Mitosis domain generalization in histopathology images—The MIDOG challenge
M Aubreville, N Stathonikos, CA Bertram, R Klopfleisch, N Ter Hoeve, ...
Medical Image Analysis 84, 102699, 2023
Multimodal angiographic assessment of cerebral arteriovenous malformations: a pilot study
R Blanc, A Seiler, T Robert, H Baharvahdat, M Lafarge, J Savatovsky, ...
Journal of neurointerventional surgery 7 (11), 841-847, 2015
Progressively growing convolutional networks for end-to-end deformable image registration
KAJ Eppenhof, MW Lafarge, JPW Pluim
Medical Imaging 2019: Image Processing 10949, 338-344, 2019
Orientation-disentangled unsupervised representation learning for computational pathology
MW Lafarge, JPW Pluim, M Veta
arXiv preprint arXiv:2008.11673, 2020
Rotation invariance and extensive data augmentation: A strategy for the mitosis domain generalization (MIDOG) challenge
MW Lafarge, VH Koelzer
Biomedical Image Registration, Domain Generalisation and Out-of-Distribution …, 2022
Towards IID representation learning and its application on biomedical data
J Wu, I Zlobec, M Lafarge, Y He, VH Koelzer
arXiv preprint arXiv:2203.00332, 2022
Towards computationally efficient prediction of molecular signatures from routine histology images
MW Lafarge, VH Koelzer
The Lancet Digital Health 3 (12), e752-e753, 2021
Inferring a third spatial dimension from 2D histological images
MW Lafarge, JPW Pluim, KAJ Eppenhof, P Moeskops, M Veta
2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018 …, 2018
Enhancing local context of histology features in vision transformers
R Wood, K Sirinukunwattana, E Domingo, A Sauer, MW Lafarge, ...
Artificial Intelligence over Infrared Images for Medical Applications and …, 2022
Multi-task learning for tissue segmentation and tumor detection in colorectal cancer histology slides
LA Schoenpflug, MW Lafarge, AL Frei, VH Koelzer
arXiv preprint arXiv:2304.03101, 2023
Fine-Grained Hard Negative Mining: Generalizing Mitosis Detection with a Fifth of the MIDOG 2022 Dataset
MW Lafarge, VH Koelzer
arXiv preprint arXiv:2301.01079, 2023
Deep learning supported mitoses counting on whole slide images: A pilot study for validating breast cancer grading in the clinical workflow
SA van Bergeijk, N Stathonikos, ND Ter Hoeve, MW Lafarge, TQ Nguyen, ...
Journal of Pathology Informatics 14, 100316, 2023
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