| nnOOD: A Framework for Benchmarking Self-supervised Anomaly Localisation Methods M Baugh, J Tan, A Vlontzos, JP Müller, B Kainz International Workshop on Uncertainty for Safe Utilization of Machine …, 2022 | 2 | 2022 |
| Zero-Shot Anomaly Detection with Pre-trained Segmentation Models M Baugh, J Batten, JP Müller, B Kainz arXiv preprint arXiv:2306.09269, 2023 | 1 | 2023 |
| Adnexal Mass Segmentation with Ultrasound Data Synthesis C Lebbos, J Barcroft, J Tan, J Müller, M Baugh, A Vlontzos, S Saso, ... International Workshop on Advances in Simplifying Medical Ultrasound, 106-116, 2022 | 1 | 2022 |
| Confidence-Aware and Self-supervised Image Anomaly Localisation J P. Müller, M Baugh, J Tan, M Dombrowski, B Kainz International Workshop on Uncertainty for Safe Utilization of Machine …, 2023 | | 2023 |
| Whole Slide Multiple Instance Learning for Predicting Axillary Lymph Node Metastasis G Shkëmbi, JP Müller, Z Li, K Breininger, P Schüffler, B Kainz MICCAI Workshop on Data Engineering in Medical Imaging, 11-20, 2023 | | 2023 |
| Many tasks make light work: Learning to localise medical anomalies from multiple synthetic tasks M Baugh, J Tan, JP Müller, M Dombrowski, J Batten, B Kainz International Conference on Medical Image Computing and Computer-Assisted …, 2023 | | 2023 |
| Simplifying Medical Ultrasound: 4th International Workshop, ASMUS 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings B Kainz, A Noble, J Schnabel, B Khanal, JP Müller, T Day Springer Nature, 2023 | | 2023 |
| Learnable Slice-to-volume Reconstruction for Motion Compensation in Fetal Magnetic Resonance Imaging C Jehn, JP Müller, B Kainz BVM Workshop, 25-31, 2023 | | 2023 |
| Pay Attention: Accuracy Versus Interpretability Trade-off in Fine-tuned Diffusion Models M Dombrowski, H Reynaud, JP Müller, M Baugh, B Kainz arXiv preprint arXiv:2303.17908, 2023 | | 2023 |
