| Concurrent Spatial and Channel Squeeze & Excitation in Fully Convolutional Networks AG Roy, N Navab, C Wachinger International Conference on Medical Image Computing and Computer-Assisted …, 2018 | 825 | 2018 |
| ReLayNet: retinal layer and fluid segmentation of macular optical coherence tomography using fully convolutional networks AG Roy, S Conjeti, SPK Karri, D Sheet, A Katouzian, C Wachinger, ... Biomedical optics express 8 (8), 3627-3642, 2017 | 549 | 2017 |
| Recalibrating Fully Convolutional Networks with Spatial and Channel 'Squeeze & Excitation' Blocks AG Roy, N Navab, C Wachinger IEEE Transactions on Medical Imaging, 2018 | 352 | 2018 |
| Braintorrent: A peer-to-peer environment for decentralized federated learning AG Roy, S Siddiqui, S Pölsterl, N Navab, C Wachinger arXiv preprint arXiv:1905.06731, 2019 | 250 | 2019 |
| QuickNAT: A fully convolutional network for quick and accurate segmentation of neuroanatomy AG Roy, S Conjeti, N Navab, C Wachinger, ADN Initiative NeuroImage 186, 713-727, 2019 | 250* | 2019 |
| Contrastive training for improved out-of-distribution detection J Winkens, R Bunel, AG Roy, R Stanforth, V Natarajan, JR Ledsam, ... arXiv preprint arXiv:2007.05566, 2020 | 194 | 2020 |
| 'Squeeze & Excite' Guided Few-Shot Segmentation of Volumetric Images AG Roy, S Siddiqui, S Pölsterl, N Navab, C Wachinger Medical Image Analysis 59, 1-12, 2019 | 130 | 2019 |
| Bayesian QuickNAT: Model uncertainty in deep whole-brain segmentation for structure-wise quality control AG Roy, S Conjeti, N Navab, C Wachinger, ... NeuroImage 195, 11-22, 2019 | 119 | 2019 |
| A simple fix to mahalanobis distance for improving near-ood detection J Ren, S Fort, J Liu, AG Roy, S Padhy, B Lakshminarayanan arXiv preprint arXiv:2106.09022, 2021 | 100 | 2021 |
| Error Corrective Boosting for Learning Fully Convolutional Networks with Limited Data AG Roy, S Conjeti, D Sheet, A Katouzian, N Navab, C Wachinger International Conference on Medical Image Computing and Computer-Assisted …, 2017 | 100* | 2017 |
| Inherent Brain Segmentation Quality Control from Fully ConvNet Monte Carlo Sampling AG Roy, S Conjeti, N Navab, C Wachinger International Conference on Medical Image Computing and Computer-Assisted …, 2018 | 91 | 2018 |
| Does your dermatology classifier know what it doesn’t know? detecting the long-tail of unseen conditions AG Roy, J Ren, S Azizi, A Loh, V Natarajan, B Mustafa, N Pawlowski, ... Medical Image Analysis 75, 102274, 2022 | 87 | 2022 |
| Deep neural ensemble for retinal vessel segmentation in fundus images towards achieving label-free angiography A Lahiri, AG Roy, D Sheet, PK Biswas 2016 38th annual international conference of the IEEE engineering in …, 2016 | 82 | 2016 |
| Multiple instance learning of deep convolutional neural networks for breast histopathology whole slide classification K Das, S Conjeti, AG Roy, J Chatterjee, D Sheet 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018 …, 2018 | 81 | 2018 |
| Classifying histopathology whole-slides using fusion of decisions from deep convolutional network on a collection of random multi-views at multi-magnification K Das, SPK Karri, AG Roy, J Chatterjee, D Sheet 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017 …, 2017 | 54 | 2017 |
| Lumen Segmentation in Intravascular Optical Coherence Tomography using Backscattering Tracked and Initialized Random Walks A Guha Roy, S Conjeti, S Carlier, P Dutta, A Kastrati, A Laine, N Navab, ... Journal of Biomedical and Health Informatics, 2015 | 41 | 2015 |
| Robust and efficient medical imaging with self-supervision S Azizi, L Culp, J Freyberg, B Mustafa, S Baur, S Kornblith, T Chen, ... arXiv preprint arXiv:2205.09723, 2022 | 36 | 2022 |
| 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 | 35 | 2019 |
| Hashing with residual networks for image retrieval S Conjeti, AG Roy, A Katouzian, N Navab Medical Image Computing and Computer Assisted Intervention− MICCAI 2017 …, 2017 | 35* | 2017 |
| 'Project & Excite' Modules for Segmentation of Volumetric Medical Scans AM Rickmann, AG Roy, I Sarasua, N Navab, C Wachinger International Conference on Medical Image Computing and Computer-Assisted …, 2019 | 32 | 2019 |
Nassir NavabProfessor of Computer Science, Technische Universität MünchenПотвърден имейл адрес: cs.tum.edu
