| Federated disentangled representation learning for unsupervised brain anomaly detection CI Bercea, B Wiestler, D Rueckert, S Albarqouni Nature Machine Intelligence 4 (8), 685-695, 2022 | 44 | 2022 |
| Feddis: Disentangled federated learning for unsupervised brain pathology segmentation CI Bercea, B Wiestler, D Rueckert, S Albarqouni arXiv preprint arXiv:2103.03705, 2021 | 41 | 2021 |
| Mask, stitch, and re-sample: Enhancing robustness and generalizability in anomaly detection through automatic diffusion models CI Bercea, M Neumayr, D Rueckert, JA Schnabel arXiv preprint arXiv:2305.19643, 2023 | 18 | 2023 |
| Reversing the Abnormal: Pseudo-Healthy Generative Networks for Anomaly Detection CI Bercea, B Wiestler, D Rueckert, JA Schnabel International Conference on Medical Image Computing and Computer-Assisted …, 2023 | 16 | 2023 |
| Generalizing Unsupervised Anomaly Detection: Towards Unbiased Pathology Screening CI Bercea, B Wiestler, D Rueckert, JA Schnabel Medical Imaging with Deep Learning, 2023 | 16 | 2023 |
| What do AEs learn? Challenging common assumptions in unsupervised anomaly detection CI Bercea, D Rueckert, JA Schnabel International Conference on Medical Image Computing and Computer-Assisted …, 2023 | 10* | 2023 |
| Confidence-aware levenberg-marquardt optimization for joint motion estimation and super-resolution C Bercea, A Maier, T Köhler 2016 IEEE International Conference on Image Processing (ICIP), 1136-1140, 2016 | 6 | 2016 |
| SHAMANN: Shared memory augmented neural networks CI Bercea, O Pauly, A Maier, FC Ghesu Information Processing in Medical Imaging: 26th International Conference …, 2019 | 4 | 2019 |
| Multispectral 3D Masked Autoencoders for Anomaly Detection in Non-Contrast Enhanced Breast MRI DM Lang, E Schwartz, CI Bercea, R Giryes, JA Schnabel MICCAI Workshop on Cancer Prevention through Early Detection, 55-67, 2023 | 2* | 2023 |
| SPA: Shape-Prior Variational Autoencoders for Unsupervised Brain Pathology Segmentation CI Bercea, B Wiestler, D Rueckert, S Albarqouni | 1 | 2022 |
| Diffusion Models for Unsupervised Anomaly Detection in Fetal Brain Ultrasound H Mykula, L Gasser, S Lobmaier, JA Schnabel, V Zimmer, CI Bercea arXiv preprint arXiv:2407.15119, 2024 | | 2024 |
| MedEdit: Counterfactual Diffusion-based Image Editing on Brain MRI MB Alaya, DM Lang, B Wiestler, JA Schnabel, CI Bercea arXiv preprint arXiv:2407.15270, 2024 | | 2024 |
| Unsupervised Analysis of Alzheimer's Disease Signatures using 3D Deformable Autoencoders MY Avci, E Chan, V Zimmer, D Rueckert, B Wiestler, JA Schnabel, ... arXiv preprint arXiv:2407.03863, 2024 | | 2024 |
| MedEdit: Counterfactual Diffusion-based Image Editing on Brain MRI M Ben Alaya, DM Lang, B Wiestler, JA Schnabel, CI Bercea arXiv e-prints, arXiv: 2407.15270, 2024 | | 2024 |
| Unsupervised Analysis of Alzheimer's Disease Signatures using 3D Deformable Autoencoders M Yigit Avci, E Chan, V Zimmer, D Rueckert, B Wiestler, JA Schnabel, ... arXiv e-prints, arXiv: 2407.03863, 2024 | | 2024 |
| Interpretable Representation Learning of Cardiac MRI via Attribute Regularization M Di Folco, CI Bercea, JA Schnabel arXiv preprint arXiv:2406.08282, 2024 | | 2024 |
| Multi-Image Visual Question Answering for Unsupervised Anomaly Detection J Li, CI Bercea, P Müller, L Felsner, S Kim, D Rueckert, B Wiestler, ... arXiv preprint arXiv:2404.07622, 2024 | | 2024 |
| Denoising Diffusion Models for 3D Healthy Brain Tissue Inpainting A Durrer, J Wolleb, F Bieder, P Friedrich, L Melie-Garcia, ... arXiv preprint arXiv:2403.14499, 2024 | | 2024 |
| Diffusion Models with Implicit Guidance for Medical Anomaly Detection CI Bercea, B Wiestler, D Rueckert, JA Schnabel arXiv preprint arXiv:2403.08464, 2024 | | 2024 |
| Towards Universal Unsupervised Anomaly Detection in Medical Imaging CI Bercea, B Wiestler, D Rueckert, JA Schnabel arXiv preprint arXiv:2401.10637, 2024 | | 2024 |
Daniel RueckertTechnical University of Munich and Imperial College LondonVerified email at tum.de
