| 2025 | MICCAI | Sequential Hard Mining: A Data-Centric Approach for Mitosis Detection. | Maxime W. Lafarge, Viktor H. Koelzer |
| 2023 | MICCAI | Detecting Cells in Histopathology Images with a ResNet Ensemble Model. | Maxime W. Lafarge, Viktor Hendrik Koelzer |
| 2023 | MICCAI | 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 |
| 2022 | MICCAI | Fine-Grained Hard-Negative Mining: Generalizing Mitosis Detection with a Fifth of the MIDOG 2022 Dataset. | Maxime W. Lafarge, Viktor H. Koelzer |
| 2022 | MICCAI | 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 |
| 2021 | MICCAI | Rotation Invariance and Extensive Data Augmentation: A Strategy for the MItosis DOmain Generalization (MIDOG) Challenge. | Maxime W. Lafarge, Viktor H. Koelzer |
| 2018 | MICCAI | 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 |
| 2017 | MICCAI | 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 |
| 2017 | MICCAI | Adversarial Training and Dilated Convolutions for Brain MRI Segmentation. | Pim Moeskops, Mitko Veta, Maxime W. Lafarge, Koen A. J. Eppenhof, Josien P. W. Pluim |