| Generalizability vs. Robustness: Investigating Medical Imaging Networks Using Adversarial Examples M Paschali, S Conjeti, F Navarro, N Navab Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 160* | 2018 |
| TeCNO: Surgical Phase Recognition with Multi-stage Temporal Convolutional Networks T Czempiel, M Paschali, M Keicher, W Simson, H Feussner, ST Kim, ... International Conference on Medical Image Computing and Computer-Assisted …, 2020 | 133 | 2020 |
| Opera: Attention-regularized transformers for surgical phase recognition T Czempiel, M Paschali, D Ostler, ST Kim, B Busam, N Navab Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021 | 73 | 2021 |
| Confidence-based out-of-distribution detection: a comparative study and analysis C Berger, M Paschali, B Glocker, K Kamnitsas Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and …, 2021 | 37 | 2021 |
| Manifold exploring data augmentation with geometric transformations for increased performance and robustness M Paschali, W Simson, AG Roy, R Göbl, C Wachinger, N Navab Information Processing in Medical Imaging: 26th International Conference …, 2019 | 37* | 2019 |
| Ultrasound-Guided Robotic Navigation with Deep Reinforcement Learning H Hase, MF Azampour, M Tirindelli, M Paschali, W Simson, ... 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020 | 34 | 2020 |
| Deep multiple instance hashing for scalable medical image retrieval S Conjeti, M Paschali, A Katouzian, N Navab Medical Image Computing and Computer Assisted Intervention− MICCAI 2017 …, 2017 | 30 | 2017 |
| Deep learning beamforming for sub-sampled ultrasound data W Simson, M Paschali, N Navab, G Zahnd 2018 IEEE International Ultrasonics Symposium (IUS), 1-4, 2018 | 25 | 2018 |
| End-to-end learning-based ultrasound reconstruction W Simson, R Göbl, M Paschali, M Krönke, K Scheidhauer, W Weber, ... arXiv preprint arXiv:1904.04696, 2019 | 20 | 2019 |
| Rethinking ultrasound augmentation: A physics-inspired approach M Tirindelli, C Eilers, W Simson, M Paschali, MF Azampour, N Navab Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021 | 18 | 2021 |
| 3DQ: Compact Quantized Neural Networks for Volumetric Whole Brain Segmentation M Paschali, S Gasperini, AG Roy, MYS Fang, N Navab International Conference on Medical Image Computing and Computer-Assisted …, 2019 | 18 | 2019 |
| Deep Learning Under the Microscope: Improving the Interpretability of Medical Imaging Neural Networks M Paschali, MF Naeem, W Simson, K Steiger, M Mollenhauer, N Navab arXiv preprint arXiv:1904.03127, 2019 | 16 | 2019 |
| Radar emitter classification with attribute-specific recurrent neural networks P Notaro, M Paschali, C Hopke, D Wittmann, N Navab arXiv preprint arXiv:1911.07683, 2019 | 14 | 2019 |
| Longitudinal quantitative assessment of COVID-19 infection progression from chest CTs ST Kim, L Goli, M Paschali, A Khakzar, M Keicher, T Czempiel, E Burian, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021 | 11 | 2021 |
| Signal clustering with class-independent segmentation S Gasperini, M Paschali, C Hopke, D Wittmann, N Navab ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 10 | 2020 |
| Investigating pulse-echo sound speed estimation in breast ultrasound with deep learning WA Simson, M Paschali, V Sideri-Lampretsa, N Navab, JJ Dahl Ultrasonics 137, 107179, 2024 | 8 | 2024 |
| Surgical workflow recognition: From analysis of challenges to architectural study T Czempiel, A Sharghi, M Paschali, N Navab, O Mohareri European Conference on Computer Vision, 556-568, 2022 | 7 | 2022 |
| Multimodal graph attention network for COVID-19 outcome prediction M Keicher, H Burwinkel, D Bani-Harouni, M Paschali, T Czempiel, ... Scientific Reports 13 (1), 19539, 2023 | 6* | 2023 |
| Data augmentation with manifold exploring geometric transformations for increased performance and robustness. arXiv 2019 M Paschali, W Simson, AG Roy, MF Naeem, R Göbl, C Wachinger, ... arXiv preprint arXiv:1901.04420, 0 | 4 | |
| Interactive segmentation for covid-19 infection quantification on longitudinal ct scans MXL Foo, ST Kim, M Paschali, L Goli, E Burian, M Makowski, R Braren, ... IEEE Access, 2023 | 3 | 2023 |
Nassir NavabProfessor of Computer Science, Technische Universität MünchenПотвърден имейл адрес: cs.tum.edu
