| Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer BE Bejnordi, M Veta, PJ Van Diest, B Van Ginneken, N Karssemeijer, ... Jama 318 (22), 2199-2210, 2017 | 3063 | 2017 |
| The future of digital health with federated learning N Rieke, J Hancox, W Li, F Milletari, H Roth, S Albarqouni, S Bakas, ... npj Digital Medicine 3 (119), 2020 | 1643 | 2020 |
| Structure-preserving color normalization and sparse stain separation for histological images A Vahadane, T Peng, A Sethi, S Albarqouni, L Wang, M Baust, K Steiger, ... IEEE transactions on medical imaging 35 (8), 1962-1971, 2016 | 735 | 2016 |
| Aggnet: deep learning from crowds for mitosis detection in breast cancer histology images S Albarqouni, C Baur, F Achilles, V Belagiannis, S Demirci, N Navab IEEE transactions on medical imaging 35 (5), 1313-1321, 2016 | 684 | 2016 |
| Deep autoencoding models for unsupervised anomaly segmentation in brain MR images C Baur, B Wiestler, S Albarqouni, N Navab Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2019 | 575 | 2019 |
| GANs for medical image analysis S Kazeminia, C Baur, A Kuijper, B van Ginneken, N Navab, S Albarqouni, ... Artificial intelligence in medicine 109, 101938, 2020 | 471 | 2020 |
| Staingan: Stain style transfer for digital histological images MT Shaban, C Baur, N Navab, S Albarqouni 2019 Ieee 16th international symposium on biomedical imaging (Isbi 2019 …, 2019 | 337 | 2019 |
| Autoencoders for Unsupervised Anomaly Segmentation in Brain MR Images: A Comparative Study C Baur, S Denner, B Wiestler, N Navab, S Albarqouni Medical Image Analysis 101952, 2021 | 326 | 2021 |
| Generating highly realistic images of skin lesions with GANs C Baur, S Albarqouni, N Navab OR 2.0 Context-Aware Operating Theaters, Computer Assisted Robotic Endoscopy …, 2018 | 202* | 2018 |
| InceptionGCN: receptive field aware graph convolutional network for disease prediction A Kazi, S Shekarforoush, S Arvind Krishna, H Burwinkel, G Vivar, ... Information Processing in Medical Imaging: 26th International Conference …, 2019 | 161 | 2019 |
| Semi-supervised deep learning for fully convolutional networks C Baur, S Albarqouni, N Navab Medical Image Computing and Computer Assisted Intervention− MICCAI 2017 …, 2017 | 155 | 2017 |
| An objective comparison of detection and segmentation algorithms for artefacts in clinical endoscopy S Ali, F Zhou, B Braden, A Bailey, S Yang, G Cheng, P Zhang, X Li, ... Scientific reports 10 (1), 2748, 2020 | 122 | 2020 |
| Capsule networks against medical imaging data challenges A Jiménez-Sánchez, S Albarqouni, D Mateus Intravascular Imaging and Computer Assisted Stenting and Large-Scale …, 2018 | 108 | 2018 |
| Inverse distance aggregation for federated learning with non-iid data Y Yeganeh, A Farshad, N Navab, S Albarqouni Domain Adaptation and Representation Transfer, and Distributed and …, 2020 | 101 | 2020 |
| Deep learning and data labeling for medical applications G Carneiro, D Mateus, L Peter, A Bradley, JMRS Tavares, V Belagiannis, ... | 100 | 2016 |
| Fairness by Learning Orthogonal Disentangled Representations MH Sarhan, N Navab, A Eslami, S Albarqouni 16th European Conference on Computer Vision (ECCV), 2020 | 88 | 2020 |
| Flamby: Datasets and benchmarks for cross-silo federated learning in realistic healthcare settings J Ogier du Terrail, SS Ayed, E Cyffers, F Grimberg, C He, R Loeb, ... Advances in Neural Information Processing Systems 35, 5315-5334, 2022 | 85 | 2022 |
| Image-to-images translation for multi-task organ segmentation and bone suppression in chest x-ray radiography M Eslami, S Tabarestani, S Albarqouni, E Adeli, N Navab, M Adjouadi IEEE transactions on medical imaging 39 (7), 2553-2565, 2020 | 85 | 2020 |
| The federated tumor segmentation (fets) challenge S Pati, U Baid, M Zenk, B Edwards, M Sheller, GA Reina, P Foley, ... arXiv preprint arXiv:2105.05874, 2021 | 82 | 2021 |
| Perceptual Embedding Consistency for Seamless Reconstruction of Tilewise Style Transfer A Lahiani, N Navab, S Albarqouni, E Klaiman Medical Image Computing and Computer Assisted Intervention, 568-576, 2019 | 69* | 2019 |
Nassir NavabProfessor of Computer Science, Technische Universität München在 cs.tum.edu 的电子邮件经过验证
