| Multi-scale deep reinforcement learning for real-time 3D-landmark detection in CT scans FC Ghesu, B Georgescu, Y Zheng, S Grbic, A Maier, J Hornegger, ... IEEE transactions on pattern analysis and machine intelligence 41 (1), 176-189, 2017 | 284 | 2017 |
| Automatic liver segmentation using an adversarial image-to-image network D Yang, D Xu, SK Zhou, B Georgescu, M Chen, S Grbic, D Metaxas, ... Medical Image Computing and Computer Assisted Intervention− MICCAI 2017 …, 2017 | 268 | 2017 |
| An artificial agent for robust image registration R Liao, S Miao, P de Tournemire, S Grbic, A Kamen, T Mansi, ... Proceedings of the AAAI conference on artificial intelligence 31 (1), 2017 | 235 | 2017 |
| Learning to recognize abnormalities in chest x-rays with location-aware dense networks S Guendel, S Grbic, B Georgescu, S Liu, A Maier, D Comaniciu Progress in Pattern Recognition, Image Analysis, Computer Vision, and …, 2019 | 197 | 2019 |
| Method and system for comprehensive patient-specific modeling of the heart RI Ionasec, I Voigt, V Mihalef, S Grbic, D Vitanovski, Y Wang, Y Zheng, ... US Patent 8,682,626, 2014 | 181 | 2014 |
| Method and System for Image Registration Using an Intelligent Artificial Agent R Liao, S Miao, P De Tournemire, J Krebs, L Zhang, B Georgescu, S Grbic, ... US Patent App. 15/587,094, 2017 | 163 | 2017 |
| Automated quantification of CT patterns associated with COVID-19 from chest CT S Chaganti, P Grenier, A Balachandran, G Chabin, S Cohen, T Flohr, ... Radiology: Artificial Intelligence 2 (4), e200048, 2020 | 151 | 2020 |
| 3d anisotropic hybrid network: Transferring convolutional features from 2d images to 3d anisotropic volumes S Liu, D Xu, SK Zhou, O Pauly, S Grbic, T Mertelmeier, J Wicklein, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 147 | 2018 |
| Complete valvular heart apparatus model from 4D cardiac CT S Grbic, R Ionasec, D Vitanovski, I Voigt, Y Wang, B Georgescu, ... Medical Image Analysis 16 (5), 1003-1014, 2012 | 105 | 2012 |
| Semiautomatically quantified tumor volume using 68Ga-PSMA-11 PET as a biomarker for survival in patients with advanced prostate cancer R Seifert, K Herrmann, J Kleesiek, M Schäfers, V Shah, Z Xu, G Chabin, ... Journal of Nuclear Medicine 61 (12), 1786-1792, 2020 | 80 | 2020 |
| Less is more: Simultaneous view classification and landmark detection for abdominal ultrasound images Z Xu, Y Huo, JH Park, B Landman, A Milkowski, S Grbic, S Zhou Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 55 | 2018 |
| Deep image-to-image recurrent network with shape basis learning for automatic vertebra labeling in large-scale 3D CT volumes D Yang, T Xiong, D Xu, SK Zhou, Z Xu, M Chen, JH Park, S Grbic, TD Tran, ... Medical Image Computing and Computer Assisted Intervention− MICCAI 2017 …, 2017 | 51 | 2017 |
| Quantifying and leveraging classification uncertainty for chest radiograph assessment FC Ghesu, B Georgescu, E Gibson, S Guendel, MK Kalra, R Singh, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 48 | 2019 |
| Towards intelligent robust detection of anatomical structures in incomplete volumetric data FC Ghesu, B Georgescu, S Grbic, A Maier, J Hornegger, D Comaniciu Medical image analysis 48, 203-213, 2018 | 44 | 2018 |
| Robust multi-scale anatomical landmark detection in incomplete 3D-CT data FC Ghesu, B Georgescu, S Grbic, AK Maier, J Hornegger, D Comaniciu Medical Image Computing and Computer Assisted Intervention− MICCAI 2017 …, 2017 | 41 | 2017 |
| Quantifying and leveraging predictive uncertainty for medical image assessment FC Ghesu, B Georgescu, A Mansoor, Y Yoo, E Gibson, RS Vishwanath, ... Medical Image Analysis 68, 101855, 2021 | 39 | 2021 |
| Self-supervised learning from 100 million medical images FC Ghesu, B Georgescu, A Mansoor, Y Yoo, D Neumann, P Patel, ... arXiv preprint arXiv:2201.01283, 2022 | 38 | 2022 |
| Class-aware adversarial lung nodule synthesis in CT images J Yang, S Liu, S Grbic, AAA Setio, Z Xu, E Gibson, G Chabin, ... 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019 …, 2019 | 37 | 2019 |
| No surprises: Training robust lung nodule detection for low-dose CT scans by augmenting with adversarial attacks S Liu, AAA Setio, FC Ghesu, E Gibson, S Grbic, B Georgescu, ... IEEE Transactions on Medical Imaging 40 (1), 335-345, 2020 | 36 | 2020 |
| Image-based computational models for TAVI planning: from CT images to implant deployment S Grbic, T Mansi, R Ionasec, I Voigt, H Houle, M John, M Schoebinger, ... Medical Image Computing and Computer-Assisted Intervention–MICCAI 2013: 16th …, 2013 | 35 | 2013 |
