Sweta Banerjee M.Sc.
Wissenschaftliche Mitarbeiterin am Fachbereich Information und Kommunikation
(mu)ROMI: Robust and Accurate Multi-Tumor, Multi-Species, Multi-Laboratory and Multi-Scanner Mitosis Detection with Large-Scale Datasets and Artificial Intelligence wissenschaftliche Mitarbeiterin
Raum D 310
Organisation
Neuste Publikationen
2026
- Banerjee, S., Weiss, V., Donovan, T. A., Fick, R., Conrad, T., Ammeling, J., … Bertram, C. A. (2026). Benchmarking Deep Learning and Vision Foundation Models for Atypical vs. Normal Mitosis Classification with Cross-Dataset Evaluation. Machine Learning for Biomedical Imaging, 3, 115–125. http://doi.org/https://doi.org/10.59275/j.melba.2026-6c1g
- Porsche, N., Müller-Diesing, F., Banerjee, S., Goncalves, M., & Aubreville, M. (2026). Filtering Scheme for Confocal Laser Endomicroscopy (CLE)-video Sequences for Self-supervised Learning. In H. Handels, K. Breininger, T. Deserno, A. Maier, K. Maier-Hein, C. Palm, & T. Tolxdorff (Hrsg.), Bildverarbeitung für die Medizin 2026 (S. 375–380). Wiesbaden: Springer Fachmedien Wiesbaden. http://doi.org/10.1007/978-3-658-51100-5_73
2025
- Banerjee, S., Weiss, V., Conrad, T., Donovan, T. A., Ammeling, J., Fick, R., … Aubreville, M. (2025). Chromosome Mask-Conditioned Generative Inpainting for Atypical Mitosis Classification. In Proceedings of the MICCAI Workshop on Computational Pathology (Bd. 316, S. 266–277). PMLR.