| 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 | 8235 | 2016 |
| Automatic liver and lesion segmentation in CT using cascaded fully convolutional neural networks and 3D conditional random fields PF Christ, MEA Elshaer, F Ettlinger, S Tatavarty, M Bickel, P Bilic, ... International Conference on Medical Image Computing and Computer-Assisted …, 2016 | 727 | 2016 |
| Hough-CNN: Deep learning for segmentation of deep brain regions in MRI and ultrasound F Milletari, SA Ahmadi, C Kroll, A Plate, V Rozanski, J Maiostre, J Levin, ... Computer Vision and Image Understanding 164, 92-102, 2017 | 416 | 2017 |
| Automatic liver and tumor segmentation of CT and MRI volumes using cascaded fully convolutional neural networks PF Christ, F Ettlinger, F Grün, MEA Elshaera, J Lipkova, S Schlecht, ... arXiv preprint arXiv:1702.05970, 2017 | 388 | 2017 |
| Statistical modeling and recognition of surgical workflow N Padoy, T Blum, SA Ahmadi, H Feussner, MO Berger, N Navab Medical image analysis 16 (3), 632-641, 2012 | 282 | 2012 |
| DeepVOG: Open-source pupil segmentation and gaze estimation in neuroscience using deep learning YH Yiu, M Aboulatta, T Raiser, L Ophey, VL Flanagin, P Zu Eulenburg, ... Journal of neuroscience methods 324, 108307, 2019 | 126 | 2019 |
| InceptionGCN: receptive field aware graph convolutional network for disease prediction A Kazi, S Shekarforoush, S Arvind Krishna, H Burwinkel, G Vivar, ... Information Processing in Medical Imaging: 26th International Conference …, 2019 | 119 | 2019 |
| Recovery of surgical workflow without explicit models SA Ahmadi, T Sielhorst, R Stauder, M Horn, H Feussner, N Navab Medical Image Computing and Computer-Assisted Intervention–MICCAI 2006: 9th …, 2006 | 110 | 2006 |
| Standardized evaluation system for left ventricular segmentation algorithms in 3D echocardiography O Bernard, JG Bosch, B Heyde, M Alessandrini, D Barbosa, ... IEEE transactions on medical imaging 35 (4), 967-977, 2015 | 100 | 2015 |
| Differentiable graph module (dgm) for graph convolutional networks A Kazi, L Cosmo, SA Ahmadi, N Navab, MM Bronstein IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (2), 1606-1617, 2022 | 97 | 2022 |
| Latent-graph learning for disease prediction L Cosmo, A Kazi, SA Ahmadi, N Navab, M Bronstein Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 52 | 2020 |
| Connectivity patterns of pallidal DBS electrodes in focal dystonia: a diffusion tensor tractography study VE Rozanski, C Vollmar, JP Cunha, SMN Tafula, SA Ahmadi, M Patzig, ... Neuroimage 84, 435-442, 2014 | 52 | 2014 |
| MR imaging differentiation of Fe2+ and Fe3+ based on relaxation and magnetic susceptibility properties O Dietrich, J Levin, SA Ahmadi, A Plate, MF Reiser, K Bötzel, A Giese, ... Neuroradiology 59, 403-409, 2017 | 51 | 2017 |
| SurvivalNet: Predicting patient survival from diffusion weighted magnetic resonance images using cascaded fully convolutional and 3D convolutional neural networks PF Christ, F Ettlinger, G Kaissis, S Schlecht, F Ahmaddy, F Grün, ... 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017 …, 2017 | 38 | 2017 |
| Graph convolution based attention model for personalized disease prediction A Kazi, S Shekarforoush, S Arvind Krishna, H Burwinkel, G Vivar, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 36 | 2019 |
| A diffusion-based connectivity map of the GPi for optimised stereotactic targeting in DBS NM da Silva, SA Ahmadi, SN Tafula, JPS Cunha, K Bötzel, C Vollmar, ... Neuroimage 144, 83-91, 2017 | 36 | 2017 |
| Midbrain segmentation in transcranial 3D ultrasound for Parkinson diagnosis SA Ahmadi, M Baust, A Karamalis, A Plate, K Boetzel, T Klein, N Navab Medical Image Computing and Computer-Assisted Intervention–MICCAI 2011: 14th …, 2011 | 31 | 2011 |
| Detection of substantia nigra echogenicities in 3D transcranial ultrasound for early diagnosis of Parkinson disease O Pauly, SA Ahmadi, A Plate, K Boetzel, N Navab Medical Image Computing and Computer-Assisted Intervention–MICCAI 2012: 15th …, 2012 | 30 | 2012 |
| MR in OR: First analysis of AR/VR visualization in 100 intra-operative Freehand SPECT acquisitions A Okur, SA Ahmadi, A Bigdelou, T Wendler, N Navab 2011 10th IEEE International Symposium on Mixed and Augmented Reality, 211-218, 2011 | 30 | 2011 |
| Patient-specific 3D ultrasound simulation based on convolutional ray-tracing and appearance optimization M Salehi, SA Ahmadi, R Prevost, N Navab, W Wein Medical Image Computing and Computer-Assisted Intervention--MICCAI 2015 …, 2015 | 29 | 2015 |
Nassir NavabProfessor of Computer Science, Technische Universität MünchenEmail verificata su cs.tum.edu
