Olof Enqvist
Olof Enqvist
Assistant Professor, Department of Signals and Systems, Chalmers University of Technology, Göteborg
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Cited by
Cited by
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
Non-sequential structure from motion
O Enqvist, F Kahl, C Olsson
2011 IEEE International Conference on Computer Vision Workshops (ICCV …, 2011
Stable structure from motion for unordered image collections
C Olsson, O Enqvist
Image Analysis: 17th Scandinavian Conference, SCIA 2011, Ystad, Sweden, May …, 2011
Optimal correspondences from pairwise constraints
O Enqvist, K Josephson, F Kahl
2009 IEEE 12th international conference on computer vision, 1295-1302, 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
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
Back driving assistant for passenger cars with trailer
C Lundquist, W Reinelt, O Enqvist
SAE Technical Paper, 2006
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
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
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
AFS-Assisted Trailer Reversing
O Enqvist
Institutionen för systemteknik, 2006
Robust optimal pose estimation
O Enqvist, F Kahl
Computer Vision–ECCV 2008: 10th European Conference on Computer Vision …, 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
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
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
Tractable algorithms for robust model estimation
O Enqvist, E Ask, F Kahl, K Åström
International Journal of Computer Vision 112, 115-129, 2015
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
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
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
Artificial intelligence‐based versus manual assessment of prostate cancer in the prostate gland: a method comparison study
MA Mortensen, P Borrelli, MH Poulsen, O Gerke, O Enqvist, J Ulén, ...
Clinical physiology and functional imaging 39 (6), 399-406, 2019
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