| Gandlf: A generally nuanced deep learning framework for scalable end-to-end clinical workflows in medical imaging S Pati, SP Thakur, M Bhalerao, S Thermos, U Baid, K Gotkowski, ... arXiv preprint arXiv:2103.01006, 2021 | 19 | 2021 |
| Detecting when pre-trained nnU-Net models fail silently for Covid-19 lung lesion segmentation C Gonzalez, K Gotkowski, A Bucher, R Fischbach, I Kaltenborn, ... Medical Image Computing and Computer Assisted Intervention – MICCAI 2021 12907, 2021 | 18 | 2021 |
| M3d-CAM: A PyTorch Library to Generate 3D Attention Maps for Medical Deep Learning K Gotkowski, C Gonzalez, A Bucher, A Mukhopadhyay Bildverarbeitung für die Medizin 2021, 217-222, 2021 | 17 | 2021 |
| Re-training deep neural networks to facilitate Boolean concept extraction C González, E Loza Mencía, J Fürnkranz Discovery Science: 20th International Conference, DS 2017, Kyoto, Japan …, 2017 | 12 | 2017 |
| What is wrong with continual learning in medical image segmentation? C Gonzalez, G Sakas, A Mukhopadhyay arXiv preprint arXiv:2010.11008, 2020 | 10 | 2020 |
| Adversarial continual learning for multi-domain hippocampal segmentation M Memmel, C Gonzalez, A Mukhopadhyay Domain Adaptation and Representation Transfer, and Affordable Healthcare and …, 2021 | 9 | 2021 |
| Self-supervised out-of-distribution detection for cardiac CMR segmentation C Gonzalez, A Mukhopadhyay Medical Imaging with Deep Learning, 205-218, 2021 | 6 | 2021 |
| How Reliable Are Out-of-Distribution Generalization Methods for Medical Image Segmentation? A Sanner, C Gonzalez, A Mukhopadhyay German Conference for Pattern Recognition 2021 13024, 604--617, 2021 | 5 | 2021 |
| Continual hippocampus segmentation with transformers A Ranem, C González, A Mukhopadhyay Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 3 | 2022 |
| Distance-based detection of out-of-distribution silent failures for Covid-19 lung lesion segmentation C González, K Gotkowski, M Fuchs, A Bucher, A Dadras, R Fischbach, ... Medical Image Analysis 82, 102596, 2022 | 2 | 2022 |
| Improving robustness and calibration in ensembles with diversity regularization HA Mehrtens, C Gonzalez, A Mukhopadhyay Pattern Recognition: 44th DAGM German Conference, DAGM GCPR 2022, Konstanz …, 2022 | 2 | 2022 |
| Practical uncertainty quantification for brain tumor segmentation M Fuchs, C Gonzalez, A Mukhopadhyay Medical Imaging with Deep Learning, 2021 | 2 | 2021 |
| i3Deep: Efficient 3D interactive segmentation with the nnU-Net K Gotkowski, C Gonzalez, I Kaltenborn, R Fischbach, A Bucher, ... International Conference on Medical Imaging with Deep Learning, 441-456, 2022 | 1 | 2022 |
| Disentanglement enables cross-domain Hippocampus Segmentation J Kalkhof, C González, A Mukhopadhyay 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI), 1-5, 2022 | 1 | 2022 |
| Med-NCA: Robust and Lightweight Segmentation with Neural Cellular Automata J Kalkhof, C González, A Mukhopadhyay arXiv preprint arXiv:2302.03473, 2023 | | 2023 |
| Task-Agnostic Continual Hippocampus Segmentation for Smooth Population Shifts C González, A Ranem, A Othman, A Mukhopadhyay Domain Adaptation and Representation Transfer: 4th MICCAI Workshop, DART …, 2022 | | 2022 |
| Lifelong nnUNet: a framework for standardized medical continual learning C Gonzalez, A Ranem, DP dos Santos, A Othman, A Mukhopadhyay | | 2022 |
| Quality monitoring of federated Covid-19 lesion segmentation C González, CL Harder, A Ranem, R Fischbach, IJ Kaltenborn, A Dadras, ... Bildverarbeitung für die Medizin 2022: Proceedings, German Workshop on …, 2022 | | 2022 |
| Continual Learning in Diagnostic Radiology: Scenarios, Challenges and Perspectives C Gonzalez, A Mukhopadhyay EuSoMII Annual Meeting 2020: How to prepare for the digital age, 6, 2020 | | 2020 |
| Detecting when pre-trained nnU-Net models fail silently for Covid-19 (preprint) C Gonzalez, K Gotkowski, A Bucher, R Fischbach, I Kaltenborn, ... | | |
Anirban MukhopadhyayTU DarmstadtVerified email at gris.tu-darmstadt.de
