| Neuman: Neural human radiance field from a single video W Jiang, KM Yi, G Samei, O Tuzel, A Ranjan European Conference on Computer Vision, 402-418, 2022 | 222 | 2022 |
| Prostate segmentation in MRI using a convolutional neural network architecture and training strategy based on statistical shape models D Karimi, G Samei, C Kesch, G Nir, SE Salcudean International journal of computer assisted radiology and surgery 13, 1211-1219, 2018 | 107 | 2018 |
| Relu strikes back: Exploiting activation sparsity in large language models I Mirzadeh, K Alizadeh, S Mehta, CC Del Mundo, O Tuzel, G Samei, ... arXiv preprint arXiv:2310.04564, 2023 | 79 | 2023 |
| A partial augmented reality system with live ultrasound and registered preoperative MRI for guiding robot-assisted radical prostatectomy G Samei, K Tsang, C Kesch, J Lobo, S Hor, O Mohareri, S Chang, ... Medical image analysis 60, 101588, 2020 | 48 | 2020 |
| Prostate segmentation in transrectal ultrasound using magnetic resonance imaging priors Q Zeng, G Samei, D Karimi, C Kesch, SS Mahdavi, P Abolmaesumi, ... International journal of computer assisted radiology and surgery 13, 749-757, 2018 | 35 | 2018 |
| Predicting liver motion using exemplar models G Samei, C Tanner, G Székely Abdominal Imaging. Computational and Clinical Applications: 4th …, 2012 | 35 | 2012 |
| Review on 4D models for organ motion compensation C Tanner, D Boye, G Samei, G Szekely Critical Reviews™ in Biomedical Engineering 40 (2), 2012 | 33 | 2012 |
| Population based modeling of respiratory lung motion and prediction from partial information D Boye, G Samei, J Schmidt, G Székely, C Tanner Medical Imaging 2013: Image Processing 8669, 221-227, 2013 | 26 | 2013 |
| Real-time FEM-based registration of 3-D to 2.5-D transrectal ultrasound images G Samei, O Goksel, J Lobo, O Mohareri, P Black, R Rohling, S Salcudean IEEE transactions on medical imaging 37 (8), 1877-1886, 2018 | 24 | 2018 |
| In vivo validation of spatio-temporal liver motion prediction from motion tracked on MR thermometry images C Tanner, Y Zur, K French, G Samei, J Strehlow, G Sat, H McLeod, ... International journal of computer assisted radiology and surgery 11, 1143-1152, 2016 | 22 | 2016 |
| Investigating anisotropic diffusion for the registration of abdominal MR images C Tanner, G Samei, G Székely 2013 IEEE 10th International Symposium on Biomedical Imaging, 484-487, 2013 | 11 | 2013 |
| Improved reconstruction of 4D-MR images by motion predictions C Tanner, G Samei, G Székely International Conference on Medical Image Computing and Computer-Assisted …, 2014 | 9 | 2014 |
| On the feasibility of transperineal 3D ultrasound image guidance for robotic radical prostatectomy P Mathur, G Samei, K Tsang, J Lobo, S Salcudean International journal of computer assisted radiology and surgery 14, 923-931, 2019 | 8 | 2019 |
| A deep learning-based method for prostate segmentation in t2-weighted magnetic resonance imaging D Karimi, G Samei, Y Shao, S Salcudean arXiv preprint arXiv:1901.09462, 2019 | 8 | 2019 |
| Robust exemplar model of respiratory liver motion and individualization using an additional breath-hold image C Tanner, G Samei, G Székely 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), 1576-1579, 2015 | 7 | 2015 |
| Border preserving skin lesion segmentation M Kamali, G Samei Medical Imaging 2008: Computer-Aided Diagnosis 6915, 1019-1027, 2008 | 7 | 2008 |
| Influence of inter-subject correspondences on liver motion predictions from population models C Tanner, M Yang, G Samei, G Székely 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), 286-289, 2016 | 6 | 2016 |
| A novel deep learning-based method for prostate segmentation in T2-weighted magnetic resonance imaging D Karimi, G Samei, Y Shao, T Salcudean Department of Electrical and Computer Engineering. The University of British …, 2019 | 4 | 2019 |
| Detection and registration of ribs in MRI using geometric and appearance models G Samei, G Székely, C Tanner Medical Image Computing and Computer-Assisted Intervention–MICCAI 2014: 17th …, 2014 | 4 | 2014 |
| Automatic segmentation of the prostate on 3D trans-rectal ultrasound images using statistical shape models and convolutional neural networks G Samei, D Karimi, C Kesch, S Salcudean arXiv preprint arXiv:2106.09662, 2021 | 3 | 2021 |
Christine TannerSenior Scientist, University of Basel, Biomaterials Science CenterVerified email at unibas.ch
