Principal Investigator: Ben Glocker
Recent Papers
- Roschewitz et al (2025) Robust image representations with counterfactual contrastive learning
- Jones et al. (2025) Rethinking Fair Representation Learning for Performance-Sensitive Tasks
- Kori et al. (2024) Identifiable Object-Centric Representation Learning via Probabilistic Slot Attention
- Jones et al. (2024) A causal perspective on dataset bias in machine learning for medical imaging
- Kori et al. (2024) Grounded Object-Centric Learning
- Ng et al. (2023) Prospective implementation of AI-assisted screen reading to improve early detection of breast cancer
Publications
2025 (2)
- Tian Xia, Matthew Sinclair, Andreas Schuh, Fabio De Sousa Ribeiro, Raghav Mehta, Rajat Rasal, Esther Puyol-Antón, Samuel Gerber, Kersten Petersen, Michiel Schaap, and Ben Glocker, Segmentor-guided Counterfactual Fine-Tuning for Locally Coherent and Targeted Image Synthesis, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2025
- James Batten, Michiel Schaap, Matthew Sinclair, Ying Bai, Ben Glocker, Vector Representations of Vessel Trees, Medical Imaging with Deep Learning (MIDL), 2025
2024 (1)
- James Batten, Matthew Sinclair, Ying Bai, Ben Glocker, Michiel Schaap, Image-to-Tree with Recursive Prompting, IEEE International Symposium on Biomedical Imaging (ISBI), 2024
2022 (1)
- Matthew Sinclair, Andreas Schuh, Karl Hahn, Kersten Petersen, Ying Bai, James Batten, Michiel Schaap, Ben Glocker, Atlas-ISTN: Joint segmentation, registration and atlas construction with image-and-spatial transformer networks, Medical Image Analysis, 2022
2019 (4)
- M Lee, K Petersen, N Pawlowski, B Glocker, M Schaap, Template Transformer Networks for Image Segmentation, International Conference on Medical Imaging with Deep Learning (MIDL), abstract track, non-archival, 2019
- Matt Lee, Ozan Oktay, Andreas Schuh, Michiel Schaap, Ben Glocker, Image-and-Spatial Transformer Networks for Structure-Guided Image Registration, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019
- Lee M, Petersen K, Pawlowski N, Glocker B, Schaap M, TeTrIS: Template Transformer Networks for Image Segmentation with Shape Priors, IEEE Transactions on Medical Imaging, 2019
- Jo Schlemper, Ozan Oktay, Michiel Schaap, Mattias Heinrich, Bernhard Kainz, Ben Glocker, Daniel Rueckert, Attention Gated Networks: Learning to Leverage Salient Regions in Medical Images, Medical Image Analysis, 2019