Domain-Adversarial Neural Networks to Address the Appearance Variability of Histopathology Images. - Maxime W. Lafarge; Josien P. W. Pluim; Koen A. J. Eppenhof; Pim Moeskops; Mitko Veta (DLMIA/ML-CDS@MICCAI, 2017)

Adversarial Training and Dilated Convolutions for Brain MRI Segmentation. - Pim Moeskops; Mitko Veta; Maxime W. Lafarge; Koen A. J. Eppenhof; Josien P. W. Pluim (DLMIA/ML-CDS@MICCAI, 2017)

Inferring a third spatial dimension from 2D histological images. - Maxime W. Lafarge; Josien P. W. Pluim; Koen A. J. Eppenhof; Pim Moeskops; Mitko Veta (ISBI, 2018)

Roto-Translation Covariant Convolutional Networks for Medical Image Analysis. - Erik J. Bekkers; Maxime W. Lafarge; Mitko Veta; Koen A. J. Eppenhof; Josien P. W. Pluim; Remco Duits (MICCAI (1), 2018)

Deformable image registration using convolutional neural networks. - Koen A. J. Eppenhof; Maxime W. Lafarge; Pim Moeskops; Mitko Veta; Josien P. W. Pluim (Image Processing, 2018)

Capturing Single-Cell Phenotypic Variation via Unsupervised Representation Learning. - Maxime W. Lafarge; Juan C. Caicedo; Anne E. Carpenter; Josien P. W. Pluim; Shantanu Singh; Mitko Veta (MIDL, 2019)

Progressively growing convolutional networks for end-to-end deformable image registration. - Koen A. J. Eppenhof; Maxime W. Lafarge; Josien P. W. Pluim (Image Processing, 2019)

Orientation-Disentangled Unsupervised Representation Learning for Computational Pathology. - Maxime W. Lafarge; Josien P. W. Pluim; Mitko Veta (CoRR, 2020)

Progressively Trained Convolutional Neural Networks for Deformable Image Registration. - Koen A. J. Eppenhof; Maxime W. Lafarge; Mitko Veta; Josien P. W. Pluim (IEEE Trans. Medical Imaging, 2020)

Rotation Invariance and Extensive Data Augmentation: A Strategy for the MItosis DOmain Generalization (MIDOG) Challenge. - Maxime W. Lafarge; Viktor H. Koelzer (MIDOG/MOOD/Learn2Reg@MICCAI, 2021)

Roto-translation equivariant convolutional networks: Application to histopathology image analysis. - Maxime W. Lafarge; Erik J. Bekkers; Josien P. W. Pluim; Remco Duits; Mitko Veta (Medical Image Anal., 2021)

Fine-Grained Hard-Negative Mining: Generalizing Mitosis Detection with a Fifth of the MIDOG 2022 Dataset. - Maxime W. Lafarge; Viktor H. Koelzer (MIDOG/DRAC@MICCAI, 2022)

Enhancing Local Context of Histology Features in Vision Transformers. - Ruby Wood; Korsuk Sirinukunwattana; Enric Domingo; Alexander Sauer; Maxime W. Lafarge; Viktor H. Koelzer; Timothy S. Maughan; Jens Rittscher (AIIIMA/MIABID@MICCAI, 2022)

Towards IID representation learning and its application on biomedical data. - Jiqing Wu; Inti Zlobec; Maxime W. Lafarge; Yukun He; Viktor H. Koelzer (MIDL, 2022)

Mitosis domain generalization in histopathology images - The MIDOG challenge. - 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; et al. (CoRR, 2022)

Detecting Cells in Histopathology Images with a ResNet Ensemble Model. - Maxime W. Lafarge; Viktor Hendrik Koelzer (GRAIL/OCELOT@MICCAI, 2023)

Joint Prediction of Response to Therapy, Molecular Traits, and Spatial Organisation in Colorectal Cancer Biopsies. - Ruby Wood; Enric Domingo; Korsuk Sirinukunwattana; Maxime W. Lafarge; Viktor H. Koelzer; Timothy S. Maughan; Jens Rittscher (MICCAI (5), 2023)

Multi-task learning for tissue segmentation and tumor detection in colorectal cancer histology slides. - Lydia A. Schoenpflug; Maxime W. Lafarge; Anja L. Frei; Viktor H. Koelzer (CoRR, 2023)

CohortFinder: an open-source tool for data-driven partitioning of biomedical image cohorts to yield robust machine learning models. - 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; et al. (CoRR, 2023)

Mitosis domain generalization in histopathology images - The MIDOG challenge. - 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; et al. (Medical Image Anal., 2023)

Domain generalization across tumor types, laboratories, and species - Insights from the 2022 edition of the Mitosis Domain Generalization Challenge. - 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; et al. (Medical Image Anal., 2024)

Sequential Hard Mining: a data-centric approach for Mitosis Detection. - Maxime W. Lafarge; Viktor H. Koelzer (CoRR, 2025)