Navab, Nassir

V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation

Milletari, F., Navab, N., & Ahmadi, S.-A. (2016) · 2016 Fourth International Conference on 3D Vision (3DV)

Medical Image Segmentation TechniquesAdvanced Neural Network Applications

Cited by 11,931

Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer

Ehteshami Bejnordi, B., Veta, M., Johannes van Diest, P., van Ginneken, B., Karssemeijer, N., Litjens, G., van der Laak, J. A. W. M., and the CAMELYON16 Consortium, Hermsen, M., Manson, Q. F., et al. (2017) · JAMA

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 3,293

Model based training, detection and pose estimation of texture-less 3D objects in heavily cluttered scenes

Hinterstoisser, S., Lepetit, V., Ilic, S., Holzer, S., Bradski, G., Konolige, K., & Navab, N. (2013) · Lecture Notes in Computer Science

Robot Manipulation and LearningAdvanced Neural Network Applications

Cited by 1,161

SSD-6D: Making RGB-Based 3D Detection and 6D Pose Estimation Great Again

Kehl, W., Manhardt, F., Tombari, F., Ilic, S., & Navab, N. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV)

Advanced Neural Network Applications3D Shape Modeling and Analysis

Cited by 1,047

Concurrent Spatial and Channel ‘Squeeze & Excitation’ in Fully Convolutional Networks

Roy, A. G., Navab, N., & Wachinger, C. (2018) · Lecture Notes in Computer Science

Advanced Neural Network ApplicationsMedical Image Segmentation Techniques

Cited by 869

CNN-SLAM: Real-Time Dense Monocular SLAM with Learned Depth Prediction

Tateno, K., Tombari, F., Laina, I., & Navab, N. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Robotics and Sensor-Based LocalizationAdvanced Vision and Imaging

Cited by 800

AggNet: Deep Learning From Crowds for Mitosis Detection in Breast Cancer Histology Images

Albarqouni, S., Baur, C., Achilles, F., Belagiannis, V., Demirci, S., & Navab, N. (2016) · IEEE Transactions on Medical Imaging

AI in cancer detectionCell Image Analysis Techniques

Cited by 606

Recalibrating Fully Convolutional Networks With Spatial and Channel “Squeeze and Excitation” Blocks

Roy, A. G., Navab, N., & Wachinger, C. (2019) · IEEE Transactions on Medical Imaging

Advanced Neural Network ApplicationsMedical Image Segmentation Techniques

Cited by 534

Statistical modeling and recognition of surgical workflow

Padoy, N., Blum, T., Ahmadi, S.-A., Feussner, H., Berger, M.-O., & Navab, N. (2012) · Medical Image Analysis

Surgical Simulation and TrainingTime Series Analysis and Forecasting

Cited by 279

BrainTorrent: A Peer-to-Peer Environment for Decentralized Federated Learning

Roy, A. G., Siddiqui, S., Pölsterl, S., Navab, N., & Wachinger, C. (2019) · arXiv

Privacy-Preserving Technologies in DataDomain Adaptation and Few-Shot Learning

Cited by 212

DeepDRR – A Catalyst for Machine Learning in Fluoroscopy-Guided Procedures

Unberath, M., Zaech, J.-N., Lee, S. C., Bier, B., Fotouhi, J., Armand, M., & Navab, N. (2018) · Lecture Notes in Computer Science

Medical Imaging and AnalysisArtificial Intelligence in Healthcare and Education

Cited by 145

Bayesian QuickNAT: model uncertainty in deep whole-brain segmentation for structure-wise quality control

Roy, A. G., Conjeti, S., Navab, N., & Wachinger, C. (2019) · NeuroImage

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 137

Large language models for structured reporting in radiology: past, present, and future

Busch, F., Hoffmann, L., dos Santos, D. P., Makowski, M. R., Saba, L., Prucker, P., Hadamitzky, M., Navab, N., Kather, J. N., Truhn, D., et al. (2024) · European Radiology

Artificial Intelligence in Healthcare and EducationRadiology practices and education

Cited by 134

Towards Unsupervised Image Captioning With Shared Multimodal Embeddings

Laina, I., Rupprecht, C., & Navab, N. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV)

Multimodal Machine Learning ApplicationsImage Retrieval and Classification Techniques

Cited by 111

Deformable 2D-3D Registration of Vascular Structures in a One View Scenario

Groher, M., Zikic, D., & Navab, N. (2009) · IEEE Transactions on Medical Imaging

Medical Image Segmentation TechniquesAdvanced Vision and Imaging

Cited by 91

How molecular imaging will enable robotic precision surgery: The role of artificial intelligence, augmented reality, and navigation

Wendler, T., van Leeuwen, F. W. B., Navab, N., & van Oosterom, M. N. (2021) · European Journal of Nuclear Medicine and Molecular Imaging

Medical Imaging Techniques and ApplicationsOptical Imaging and Spectroscopy Techniques

Cited by 73

Optical flow estimation with uncertainties through dynamic MRFs

Glocker, B., Paragios, N., Komodakis, N., Tziritas, G., & Navab, N. (2008) · 2008 IEEE Conference on Computer Vision and Pattern Recognition

Advanced Vision and ImagingMedical Image Segmentation Techniques

Cited by 69

Enabling machine learning in X-ray-based procedures via realistic simulation of image formation

Unberath, M., Zaech, J.-N., Gao, C., Bier, B., Goldmann, F., Lee, S. C., Fotouhi, J., Taylor, R., Armand, M., & Navab, N. (2019) · International Journal of Computer Assisted Radiology and Surgery

Medical Image Segmentation TechniquesArtificial Intelligence in Healthcare and Education

Cited by 63

3D reconstruction from projection matrices in a C-arm based 3D-angiography system

Navab, N., Bani-Hashemi, A., Nadar, M. S., Wiesent, K., Durlak, P., Brunner, T., Barth, K., & Graumann, R. (1998) · Lecture Notes in Computer Science

Advanced X-ray and CT ImagingMedical Imaging Techniques and Applications

Cited by 50

A Taxonomy and Library for Visualizing Learned Features in Convolutional Neural Networks

Grün, F., Rupprecht, C., Navab, N., & Tombari, F. (2016) · arXiv

Advanced Neural Network ApplicationsExplainable Artificial Intelligence (XAI)

Cited by 49

Multi-task Learning of a Deep K-Nearest Neighbour Network for Histopathological Image Classification and Retrieval

Peng, T., Boxberg, M., Weichert, W., Navab, N., & Marr, C. (2019) · Lecture Notes in Computer Science

AI in cancer detectionImage Retrieval and Classification Techniques

Cited by 48

Superman-like X-ray vision: Towards brain-computer interfaces for medical augmented reality

Blum, T., Stauder, R., Euler, E., & Navab, N. (2012) · 2012 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)

EEG and Brain-Computer InterfacesAugmented Reality Applications

Cited by 44

Learning to detect anatomical landmarks of the pelvis in X-rays from arbitrary views

Bier, B., Goldmann, F., Zaech, J.-N., Fotouhi, J., Hegeman, R., Grupp, R., Armand, M., Osgood, G., Navab, N., Maier, A., et al. (2019) · International Journal of Computer Assisted Radiology and Surgery

Medical Imaging and AnalysisMedical Image Segmentation Techniques

Cited by 43

Towards Fully Automatic X-Ray to CT Registration

Esteban, J., Grimm, M., Unberath, M., Zahnd, G., & Navab, N. (2019) · Lecture Notes in Computer Science

Medical Image Segmentation TechniquesMedical Imaging and Analysis

Cited by 38