| City-scale localization for cameras with known vertical direction L Svärm, O Enqvist, F Kahl, M Oskarsson IEEE transactions on pattern analysis and machine intelligence 39 (7), 1455-1461, 2016 | 233 | 2016 |
| Non-sequential structure from motion O Enqvist, F Kahl, C Olsson 2011 IEEE International Conference on Computer Vision Workshops (ICCV …, 2011 | 167 | 2011 |
| Stable structure from motion for unordered image collections C Olsson, O Enqvist Image Analysis: 17th Scandinavian Conference, SCIA 2011, Ystad, Sweden, May …, 2011 | 154 | 2011 |
| Optimal correspondences from pairwise constraints O Enqvist, K Josephson, F Kahl 2009 IEEE 12th international conference on computer vision, 1295-1302, 2009 | 132 | 2009 |
| Deep learning for segmentation of 49 selected bones in CT scans: first step in automated PET/CT-based 3D quantification of skeletal metastases SL Belal, M Sadik, R Kaboteh, O Enqvist, J Ulén, MH Poulsen, ... European journal of radiology 113, 89-95, 2019 | 128 | 2019 |
| Accurate Localization and Pose Estimation for Large 3D Models L Svärm, O Enqvist, M Oskarsson, F Kahl Conference on Computer Vision and Pattern Recognition (CVPR), 2014 | 115 | 2014 |
| A polynomial-time bound for matching and registration with outliers C Olsson, O Enqvist, F Kahl 2008 IEEE Conference on Computer Vision and Pattern Recognition, 1-8, 2008 | 91 | 2008 |
| Back driving assistant for passenger cars with trailer C Lundquist, W Reinelt, O Enqvist SAE Technical Paper, 2006 | 91 | 2006 |
| RECOMIA—a cloud-based platform for artificial intelligence research in nuclear medicine and radiology E Trägårdh, P Borrelli, R Kaboteh, T Gillberg, J Ulén, O Enqvist, ... EJNMMI physics 7, 1-12, 2020 | 85 | 2020 |
| Robust fitting for multiple view geometry O Enqvist, E Ask, F Kahl, K Åström Computer Vision–ECCV 2012: 12th European Conference on Computer Vision …, 2012 | 75 | 2012 |
| AFS-Assisted Trailer Reversing O Enqvist Institutionen för systemteknik, 2006 | 72 | 2006 |
| Robust optimal pose estimation O Enqvist, F Kahl Computer Vision–ECCV 2008: 10th European Conference on Computer Vision …, 2008 | 56 | 2008 |
| Deep learning‐based quantification of PET/CT prostate gland uptake: association with overall survival E Polymeri, M Sadik, R Kaboteh, P Borrelli, O Enqvist, J Ulén, M Ohlsson, ... Clinical physiology and functional imaging 40 (2), 106-113, 2020 | 53 | 2020 |
| Artificial intelligence-aided CT segmentation for body composition analysis: a validation study P Borrelli, R Kaboteh, O Enqvist, J Ulén, E Trägårdh, H Kjölhede, ... European Radiology Experimental 5, 1-6, 2021 | 43 | 2021 |
| Denoising of scintillation camera images using a deep convolutional neural network: a Monte Carlo simulation approach D Minarik, O Enqvist, E Trägårdh Journal of Nuclear Medicine 61 (2), 298-303, 2020 | 38 | 2020 |
| Optimal geometric fitting under the truncated L2-norm E Ask, O Enqvist, F Kahl Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2013 | 38 | 2013 |
| Tractable algorithms for robust model estimation O Enqvist, E Ask, F Kahl, K Åström International Journal of Computer Vision 112, 115-129, 2015 | 35 | 2015 |
| 3D skeletal uptake of 18F sodium fluoride in PET/CT images is associated with overall survival in patients with prostate cancer S Lindgren Belal, M Sadik, R Kaboteh, N Hasani, O Enqvist, L Svärm, ... EJNMMI research 7, 1-8, 2017 | 32 | 2017 |
| Automatic pericardium segmentation and quantification of epicardial fat from computed tomography angiography A Norlén, J Alvén, D Molnar, O Enqvist, RR Norrlund, J Brandberg, ... Journal of Medical Imaging 3 (3), 034003-034003, 2016 | 32 | 2016 |
| Artificial intelligence‐based detection of lymph node metastases by PET/CT predicts prostate cancer‐specific survival P Borrelli, M Larsson, J Ulén, O Enqvist, E Trägårdh, MH Poulsen, ... Clinical Physiology and Functional Imaging 41 (1), 62-67, 2021 | 31 | 2021 |
