| 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 | 845 | 2017 |
| 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 | 318 | 2016 |
| 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 | 136 | 2016 |
| Deep autoencoding models for unsupervised anomaly segmentation in brain MR images C Baur, B Wiestler, S Albarqouni, N Navab International MICCAI Brainlesion Workshop, 161-169, 2018 | 99 | 2018 |
| 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 | 64 | 2019 |
| Semi-supervised deep learning for fully convolutional networks C Baur, S Albarqouni, N Navab International Conference on Medical Image Computing and Computer-Assisted …, 2017 | 60 | 2017 |
| GANs for medical image analysis S Kazeminia, C Baur, A Kuijper, B van Ginneken, N Navab, S Albarqouni, ... Artificial Intelligence in Medicine, 101938, 2020 | 57 | 2020 |
| 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 | 42* | 2018 |
| Capsule networks against medical imaging data challenges A Jiménez-Sánchez, S Albarqouni, D Mateus Intravascular Imaging and Computer Assisted Stenting and Large-Scale …, 2018 | 31 | 2018 |
| Structure-preserved color normalization for histological images A Vahadane, T Peng, S Albarqouni, M Baust, K Steiger, AM Schlitter, ... 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), 1012-1015, 2015 | 31 | 2015 |
| Parsing human skeletons in an operating room V Belagiannis, X Wang, HBB Shitrit, K Hashimoto, R Stauder, Y Aoki, ... Machine Vision and Applications 27 (7), 1035-1046, 2016 | 22 | 2016 |
| 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), 1-15, 2020 | 20 | 2020 |
| Domain and geometry agnostic CNNs for left atrium segmentation in 3D ultrasound MA Degel, N Navab, S Albarqouni International Conference on Medical Image Computing and Computer-Assisted …, 2018 | 16 | 2018 |
| Intraoperative stent segmentation in X-ray fluoroscopy for endovascular aortic repair K Breininger, S Albarqouni, T Kurzendorfer, M Pfister, M Kowarschik, ... International journal of computer assisted radiology and surgery 13 (8 …, 2018 | 13 | 2018 |
| Automatic classification of proximal femur fractures based on attention models A Kazi, S Albarqouni, AJ Sanchez, S Kirchhoff, P Biberthaler, N Navab, ... International Workshop on Machine Learning in Medical Imaging, 70-78, 2017 | 13 | 2017 |
| InceptionGCN: receptive field aware graph convolutional network for disease prediction A Kazi, S Shekarforoush, SA Krishna, H Burwinkel, G Vivar, K Kortüm, ... International Conference on Information Processing in Medical Imaging, 73-85, 2019 | 12 | 2019 |
| Scene coordinate and correspondence learning for image-based localization M Bui, S Albarqouni, S Ilic, N Navab arXiv preprint arXiv:1805.08443, 2018 | 11 | 2018 |
| X-ray in-depth decomposition: Revealing the latent structures S Albarqouni, J Fotouhi, N Navab International Conference on Medical Image Computing and Computer-Assisted …, 2017 | 11 | 2017 |
| Cathnets: detection and single-view depth prediction of catheter electrodes C Baur, S Albarqouni, S Demirci, N Navab, P Fallavollita International Conference on Medical Imaging and Augmented Reality, 38-49, 2016 | 11 | 2016 |
| Fusing unsupervised and supervised deep learning for white matter lesion segmentation C Baur, B Wiestler, S Albarqouni, N Navab International Conference on Medical Imaging with Deep Learning, 63-72, 2019 | 9 | 2019 |
Nassir NavabProfessor of Computer Science, Technische Universität MünchenVerified email at cs.tum.edu
