| A closer look at domain shift for deep learning in histopathology K Stacke, G Eilertsen, J Unger, C Lundström arXiv preprint arXiv:1909.11575, 2019 | 45 | 2019 |
| Measuring domain shift for deep learning in histopathology K Stacke, G Eilertsen, J Unger, C Lundström IEEE journal of biomedical and health informatics 25 (2), 325-336, 2020 | 42 | 2020 |
| Proactive construction of an annotated imaging database for artificial intelligence training CB Stadler, M Lindvall, C Lundström, A Bodén, K Lindman, J Rose, ... Journal of digital imaging 34 (1), 105-115, 2021 | 7 | 2021 |
| A study of deep learning colon cancer detection in limited data access scenarios A Tsirikoglou, K Stacke, G Eilertsen, M Lindvall, J Unger arXiv preprint arXiv:2005.10326, 2020 | 6 | 2020 |
| Primary tumor and inter-organ augmentations for supervised lymph node colon adenocarcinoma metastasis detection A Tsirikoglou, K Stacke, G Eilertsen, J Unger International Conference on Medical Image Computing and Computer-Assisted …, 2021 | 5 | 2021 |
| Evaluation of contrastive predictive coding for histopathology applications K Stacke, C Lundström, J Unger, G Eilertsen Machine Learning for Health, 328-340, 2020 | 4 | 2020 |
| Learning representations with contrastive self-supervised learning for histopathology applications K Stacke, J Unger, C Lundström, G Eilertsen arXiv preprint arXiv:2112.05760, 2021 | 2 | 2021 |
| Combatting out-of-distribution errors using model-agnostic meta-learning for digital pathology F Fagerblom, K Stacke, J Molin Medical Imaging 2021: Digital Pathology 11603, 186-192, 2021 | 1 | 2021 |
| Automatic Brain Segmentation into Substructures Using Quantitative MRI K Stacke | | 2016 |
Jonas UngerProfessor, division for Media and Information Technology, Linköping University, SwedenVerified email at liu.se
