Nassir Navab
Nassir Navab
Professor of Computer Science, Technische Universität München
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TitelZitiert vonJahr
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
Advanced medical displays: A literature review of augmented reality
T Sielhorst, M Feuerstein, N Navab
Journal of Display Technology 4 (4), 451-467, 2008
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
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
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