Maxime W. Lafarge

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 30

Top Topics

Learning Models

Deformable Image Registration

Convolutional Network

Top Venues

Medical Image Anal.

DLMIA/ML-CDS@MICCAI

Publications

Marc Aubreville, Nikolas Stathonikos, Taryn A. Donovan, Robert Klopfleisch, Jonas Ammeling, Jonathan Ganz, Frauke Wilm, Mitko Veta, Samir Jabari, Markus Eckstein, Jonas Annuscheit, Christian Krumnow, Engin Bozaba, Sercan Çayir, Hongyan Gu, Xiang Anthony Chen, Mostafa Jahanifar, Adam Shephard, Satoshi Kondo, Satoshi Kasai, Sujatha Kotte, VG Saipradeep, Maxime W. Lafarge, Viktor H. Koelzer, Ziyue Wang, Yongbing Zhang, Sen Yang, Xiyue Wang, Katharina Breininger, Christof A. Bertram
Domain generalization across tumor types, laboratories, and species - Insights from the 2022 edition of the Mitosis Domain Generalization Challenge. Medical Image Anal. 94 (2024)
Marc Aubreville, Nikolas Stathonikos, Taryn A. Donovan, Robert Klopfleisch, Jonathan Ganz, Jonas Ammeling, Frauke Wilm, Mitko Veta, Samir Jabari, Markus Eckstein, Jonas Annuscheit, Christian Krumnow, Engin Bozaba, Sercan Cayir, Hongyan Gu, Xiang 'Anthony' Chen, Mostafa Jahanifar, Adam Shephard, Satoshi Kondo, Satoshi Kasai, Sujatha Kotte, VG Saipradeep, Maxime W. Lafarge, Viktor H. Koelzer, Ziyue Wang, Yongbing Zhang, Sen Yang, Xiyue Wang, Katharina Breininger, Christof A. Bertram
Domain generalization across tumor types, laboratories, and species - insights from the 2022 edition of the Mitosis Domain Generalization Challenge. CoRR (2023)
Lydia A. Schoenpflug, Maxime W. Lafarge, Anja L. Frei, Viktor H. Koelzer
Multi-task learning for tissue segmentation and tumor detection in colorectal cancer histology slides. CoRR (2023)
Fan Fan, Georgia Martinez, Thomas DeSilvio, John Shin, Yijiang Chen, Bangchen Wang, Takaya Ozeki, Maxime W. Lafarge, Viktor H. Koelzer, Laura Barisoni, Anant Madabhushi, Satish E. Viswanath, Andrew Janowczyk
CohortFinder: an open-source tool for data-driven partitioning of biomedical image cohorts to yield robust machine learning models. CoRR (2023)
Marc Aubreville, Nikolas Stathonikos, Christof A. Bertram, Robert Klopfleisch, Natalie ter Hoeve, Francesco Ciompi, Frauke Wilm, Christian Marzahl, Taryn A. Donovan, Andreas K. Maier, Jack Breen, Nishant Ravikumar, Youjin Chung, Jinah Park, Ramin Nateghi, Fattaneh Pourakpour, Rutger H. J. Fick, Saima Ben Hadj, Mostafa Jahanifar, Adam Shephard, Jakob Dexl, Thomas Wittenberg, Satoshi Kondo, Maxime W. Lafarge, Viktor H. Koelzer, Jingtang Liang, Yubo Wang, Xi Long, Jingxin Liu, Salar Razavi, April Khademi, Sen Yang, Xiyue Wang, Ramona Erber, Andrea Klang, Karoline Lipnik, Pompei Bolfa, Michael J. Dark, Gabriel Wasinger, Mitko Veta, Katharina Breininger
Mitosis domain generalization in histopathology images - The MIDOG challenge. Medical Image Anal. 84 (2023)
Maxime W. Lafarge, Viktor Hendrik Koelzer
Detecting Cells in Histopathology Images with a ResNet Ensemble Model. GRAIL/OCELOT@MICCAI (2023)
Ruby Wood, Enric Domingo, Korsuk Sirinukunwattana, Maxime W. Lafarge, Viktor H. Koelzer, Timothy S. Maughan, Jens Rittscher
Joint Prediction of Response to Therapy, Molecular Traits, and Spatial Organisation in Colorectal Cancer Biopsies. MICCAI (5) (2023)
Maxime W. Lafarge, Viktor H. Koelzer
Fine-Grained Hard Negative Mining: Generalizing Mitosis Detection with a Fifth of the MIDOG 2022 Dataset. CoRR (2023)
Jiqing Wu, Inti Zlobec, Maxime W. Lafarge, Yukun He, Viktor H. Koelzer
Towards IID representation learning and its application on biomedical data. CoRR (2022)
Ruby Wood, Korsuk Sirinukunwattana, Enric Domingo, Alexander Sauer, Maxime W. Lafarge, Viktor H. Koelzer, Timothy S. Maughan, Jens Rittscher
Enhancing Local Context of Histology Features in Vision Transformers. AIIIMA/MIABID@MICCAI (2022)
Jiqing Wu, Inti Zlobec, Maxime W. Lafarge, Yukun He, Viktor H. Koelzer
Towards IID representation learning and its application on biomedical data. MIDL (2022)
Marc Aubreville, Nikolas Stathonikos, Christof A. Bertram, Robert Klopfleisch, Natalie D. ter Hoeve, Francesco Ciompi, Frauke Wilm, Christian Marzahl, Taryn A. Donovan, Andreas K. Maier, Jack Breen, Nishant Ravikumar, Youjin Chung, Jinah Park, Ramin Nateghi, Fattaneh Pourakpour, Rutger H. J. Fick, Saima Ben Hadj, Mostafa Jahanifar, Nasir M. Rajpoot, Jakob Dexl, Thomas Wittenberg, Satoshi Kondo, Maxime W. Lafarge, Viktor H. Koelzer, Jingtang Liang, Yubo Wang, Xi Long, Jingxin Liu, Salar Razavi, April Khademi, Sen Yang, Xiyue Wang, Mitko Veta, Katharina Breininger
Mitosis domain generalization in histopathology images - The MIDOG challenge. CoRR (2022)
Maxime W. Lafarge, Viktor H. Koelzer
Fine-Grained Hard-Negative Mining: Generalizing Mitosis Detection with a Fifth of the MIDOG 2022 Dataset. MIDOG/DRAC@MICCAI (2022)
Maxime W. Lafarge, Viktor H. Koelzer
Rotation Invariance and Extensive Data Augmentation: A Strategy for the MItosis DOmain Generalization (MIDOG) Challenge. MIDOG/MOOD/Learn2Reg@MICCAI (2021)
Maxime W. Lafarge, Erik J. Bekkers, Josien P. W. Pluim, Remco Duits, Mitko Veta
Roto-translation equivariant convolutional networks: Application to histopathology image analysis. Medical Image Anal. 68 (2021)
Maxime W. Lafarge, Viktor H. Koelzer
Rotation Invariance and Extensive Data Augmentation: a strategy for the Mitosis Domain Generalization (MIDOG) Challenge. CoRR (2021)
Maxime W. Lafarge, Josien P. W. Pluim, Mitko Veta
Orientation-Disentangled Unsupervised Representation Learning for Computational Pathology. CoRR (2020)
Maxime W. Lafarge, Erik J. Bekkers, Josien P. W. Pluim, Remco Duits, Mitko Veta
Roto-Translation Equivariant Convolutional Networks: Application to Histopathology Image Analysis. CoRR (2020)
Koen A. J. Eppenhof, Maxime W. Lafarge, Mitko Veta, Josien P. W. Pluim
Progressively Trained Convolutional Neural Networks for Deformable Image Registration. IEEE Trans. Medical Imaging 39 (5) (2020)
Koen A. J. Eppenhof, Maxime W. Lafarge, Josien P. W. Pluim
Progressively growing convolutional networks for end-to-end deformable image registration. Medical Imaging: Image Processing (2019)
Maxime W. Lafarge, Juan C. Caicedo, Anne E. Carpenter, Josien P. W. Pluim, Shantanu Singh, Mitko Veta
Capturing Single-Cell Phenotypic Variation via Unsupervised Representation Learning. MIDL (2019)
Maxime W. Lafarge, Josien P. W. Pluim, Koen A. J. Eppenhof, Pim Moeskops, Mitko Veta
Inferring a third spatial dimension from 2D histological images. ISBI (2018)
Erik J. Bekkers, Maxime W. Lafarge, Mitko Veta, Koen A. J. Eppenhof, Josien P. W. Pluim, Remco Duits
Roto-Translation Covariant Convolutional Networks for Medical Image Analysis. MICCAI (1) (2018)
Maxime W. Lafarge, Josien P. W. Pluim, Koen A. J. Eppenhof, Pim Moeskops, Mitko Veta
Inferring a Third Spatial Dimension from 2D Histological Images. CoRR (2018)
Koen A. J. Eppenhof, Maxime W. Lafarge, Pim Moeskops, Mitko Veta, Josien P. W. Pluim
Deformable image registration using convolutional neural networks. Medical Imaging: Image Processing (2018)
Erik J. Bekkers, Maxime W. Lafarge, Mitko Veta, Koen A. J. Eppenhof, Josien P. W. Pluim, Remco Duits
Roto-Translation Covariant Convolutional Networks for Medical Image Analysis. CoRR (2018)
Maxime W. Lafarge, Josien P. W. Pluim, Koen A. J. Eppenhof, Pim Moeskops, Mitko Veta
Domain-Adversarial Neural Networks to Address the Appearance Variability of Histopathology Images. DLMIA/ML-CDS@MICCAI (2017)
Maxime W. Lafarge, Josien P. W. Pluim, Koen A. J. Eppenhof, Pim Moeskops, Mitko Veta
Domain-adversarial neural networks to address the appearance variability of histopathology images. CoRR (2017)
Pim Moeskops, Mitko Veta, Maxime W. Lafarge, Koen A. J. Eppenhof, Josien P. W. Pluim
Adversarial training and dilated convolutions for brain MRI segmentation. CoRR (2017)
Pim Moeskops, Mitko Veta, Maxime W. Lafarge, Koen A. J. Eppenhof, Josien P. W. Pluim
Adversarial Training and Dilated Convolutions for Brain MRI Segmentation. DLMIA/ML-CDS@MICCAI (2017)