| V-net: Fully convolutional neural networks for volumetric medical image segmentation F Milletari, N Navab, SA Ahmadi 2016 fourth international conference on 3D vision (3DV), 565-571, 2016 | 4091 | 2016 |
| 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 | 1427 | 2017 |
| Deeper depth prediction with fully convolutional residual networks I Laina, C Rupprecht, V Belagiannis, F Tombari, N Navab 2016 Fourth international conference on 3D vision (3DV), 239-248, 2016 | 1268 | 2016 |
| Model based training, detection and pose estimation of texture-less 3d objects in heavily cluttered scenes S Hinterstoisser, V Lepetit, S Ilic, S Holzer, G Bradski, K Konolige, ... Asian conference on computer vision, 548-562, 2012 | 843 | 2012 |
| Model globally, match locally: Efficient and robust 3D object recognition B Drost, M Ulrich, N Navab, S Ilic 2010 IEEE computer society conference on computer vision and pattern …, 2010 | 810 | 2010 |
| Tissue classification as a potential approach for attenuation correction in whole-body PET/MRI: evaluation with PET/CT data A Martinez-Möller, M Souvatzoglou, G Delso, RA Bundschuh, ... Journal of nuclear medicine 50 (4), 520-526, 2009 | 726 | 2009 |
| Ssd-6d: Making rgb-based 3d detection and 6d pose estimation great again W Kehl, F Manhardt, F Tombari, S Ilic, N Navab Proceedings of the IEEE international conference on computer vision, 1521-1529, 2017 | 548 | 2017 |
| Gradient response maps for real-time detection of textureless objects S Hinterstoisser, C Cagniart, S Ilic, P Sturm, N Navab, P Fua, V Lepetit IEEE transactions on pattern analysis and machine intelligence 34 (5), 876-888, 2011 | 527 | 2011 |
| Dense image registration through MRFs and efficient linear programming B Glocker, N Komodakis, G Tziritas, N Navab, N Paragios Medical image analysis 12 (6), 731-741, 2008 | 516 | 2008 |
| Cnn-slam: Real-time dense monocular slam with learned depth prediction K Tateno, F Tombari, I Laina, N Navab Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 506 | 2017 |
| Multimodal templates for real-time detection of texture-less objects in heavily cluttered scenes S Hinterstoisser, S Holzer, C Cagniart, S Ilic, K Konolige, N Navab, ... 2011 international conference on computer vision, 858-865, 2011 | 495 | 2011 |
| 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 | 439 | 2016 |
| Evaluation of registration methods on thoracic CT: the EMPIRE10 challenge K Murphy, B Van Ginneken, JM Reinhardt, S Kabus, K Ding, X Deng, ... IEEE transactions on medical imaging 30 (11), 1901-1920, 2011 | 439 | 2011 |
| Automatic CT-ultrasound registration for diagnostic imaging and image-guided intervention W Wein, S Brunke, A Khamene, MR Callstrom, N Navab Medical image analysis 12 (5), 577-585, 2008 | 405 | 2008 |
| Visual marker detection and decoding in ar systems: A comparative study X Zhang, S Fronz, N Navab Proceedings. International Symposium on Mixed and Augmented Reality, 97-106, 2002 | 349 | 2002 |
| Advanced medical displays: A literature review of augmented reality T Sielhorst, M Feuerstein, N Navab Journal of Display Technology 4 (4), 451-467, 2008 | 325 | 2008 |
| Single-point active alignment method (SPAAM) for optical see-through HMD calibration for augmented reality M Tuceryan, Y Genc, N Navab Presence: Teleoperators & Virtual Environments 11 (3), 259-276, 2002 | 313 | 2002 |
| 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 | 305 | 2017 |
| Dominant orientation templates for real-time detection of texture-less objects S Hinterstoisser, V Lepetit, S Ilic, P Fua, N Navab 2010 IEEE Computer Society Conference on Computer Vision and Pattern …, 2010 | 305 | 2010 |
| 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 | 304 | 2018 |
Federico TombariGoogle, TU MunichVerified email at in.tum.de
