| 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 | 1291 | 2016 |
| 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 | 602 | 2009 |
| 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 | 544 | 2010 |
| 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 | 537 | 2016 |
| 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 | 461 | 2008 |
| 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 | 449 | 2017 |
| 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 | 436 | 2012 |
| 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 | 359 | 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 | 358 | 2008 |
| 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 | 347 | 2011 |
| 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 | 312 | 2011 |
| Visual marker detection and decoding in ar systems: A comparative study X Zhang, S Fronz, N Navab Proceedings of the 1st International Symposium on Mixed and Augmented …, 2002 | 288 | 2002 |
| Enhanced 3-D-reconstruction algorithm for C-arm systems suitable for interventional procedures K Wiesent, K Barth, N Navab, P Durlak, T Brunner, O Schuetz, W Seissler IEEE transactions on medical imaging 19 (5), 391-403, 2000 | 259 | 2000 |
| 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 | 257 | 2010 |
| 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 | 255 | 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 | 229 | 2008 |
| 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 | 227 | 2016 |
| 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 | 222 | 2017 |
| Human skeleton tracking from depth data using geodesic distances and optical flow LA Schwarz, A Mkhitaryan, D Mateus, N Navab Image and Vision Computing 30 (3), 217-226, 2012 | 209 | 2012 |
| Patient-specific modeling and quantification of the aortic and mitral valves from 4-D cardiac CT and TEE RI Ionasec, I Voigt, B Georgescu, Y Wang, H Houle, F Vega-Higuera, ... IEEE transactions on medical imaging 29 (9), 1636-1651, 2010 | 201 | 2010 |
Federico TombariTU Munich, Pointu3D, Open PerceptionBestätigte E-Mail-Adresse bei in.tum.de
