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Silas Ørting
Silas Ørting
Post Doc, Computer Science, University of Copenhagen
Geverifieerd e-mailadres voor di.ku.dk
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A survey of crowdsourcing in medical image analysis
S Ørting, A Doyle, A van Hilten, M Hirth, O Inel, CR Madan, P Mavridis, ...
arXiv preprint arXiv:1902.09159, 2019
452019
Deep learning from label proportions for emphysema quantification
G Bortsova, F Dubost, S Ørting, I Katramados, L Hogeweg, L Thomsen, ...
International Conference on Medical Image Computing and Computer-Assisted …, 2018
212018
Detecting emphysema with multiple instance learning
SN Ørting, J Petersen, LH Thomsen, MMW Wille, M De Bruijne
2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018 …, 2018
112018
Training shortest-path tractography: Automatic learning of spatial priors
N Kasenburg, M Liptrot, NL Reislev, SN Ørting, M Nielsen, E Garde, ...
NeuroImage 130, 63-76, 2016
112016
Classification of volumetric images using multi-instance learning and extreme value theorem
R Tennakoon, G Bortsova, S Ørting, AK Gostar, MMW Wille, Z Saghir, ...
IEEE transactions on medical imaging 39 (4), 854-865, 2019
82019
Crowdsourced emphysema assessment
SN Ørting, V Cheplygina, J Petersen, LH Thomsen, MMW Wille, M Bruijne
Intravascular Imaging and Computer Assisted Stenting, and Large-Scale …, 2017
82017
A cross-center smoothness prior for variational Bayesian brain tissue segmentation
WM Kouw, SN Ørting, J Petersen, KS Pedersen, M Bruijne
International Conference on Information Processing in Medical Imaging, 360-371, 2019
62019
Locally orderless tensor networks for classifying two-and three-dimensional medical images
R Selvan, S Ørting, EB Dam
arXiv preprint arXiv:2009.12280, 2020
52020
Quantifying emphysema extent from weakly labeled CT scans of the lungs using label proportions learning
SN Ørting, J Petersen, MMW Wille, LH Thomsen, M de Bruijne
MICCAI PIA, 31-42, 2016
52016
Learning to quantify emphysema extent: What labels do we need?
SN Ørting, J Petersen, LH Thomsen, MMW Wille, M de Bruijne
IEEE Journal of Biomedical and Health Informatics 24 (4), 1149-1159, 2019
22019
Feature learning based on visual similarity triplets in medical image analysis: A case study of emphysema in chest CT scans
S Nyboe Ørting, J Petersen, V Cheplygina, LH Thomsen, MMW Wille, ...
Intravascular Imaging and Computer Assisted Stenting and Large-Scale …, 2018
22018
Morphology on categorical distributions
SN Ørting, HJT Stephensen, J Sporring
arXiv preprint arXiv:2012.07315, 2020
12020
Multi-layered tensor networks for image classification
R Selvan, S Ørting, EB Dam
arXiv preprint arXiv:2011.06982, 2020
12020
A small note on variation in segmentation annotations
SN Ørting
arXiv preprint arXiv:2012.01975, 2020
2020
A small note on variation in segmentation annotations
S Nyboe Ørting
arXiv e-prints, arXiv: 2012.01975, 2020
2020
Morphology on categorical distributions
S Nyboe Ørting, HJ Teglbjærg Stephensen, J Sporring
arXiv e-prints, arXiv: 2012.07315, 2020
2020
Learning to quantify emphysema extent: What labels do we need?
S Nyboe Ørting, J Petersen, LH Thomsen, MMW Wille, M de Bruijne
arXiv e-prints, arXiv: 1810.07433, 2018
2018
Feature learning based on visual similarity triplets in medical image analysis
SN Ørting, J Petersen, V Cheplygina, LH Thomsen, MM Wille
Assessing emphysema in CT scans of the lungs
SN Ørting
Graph-based fibre tractography computing shortest paths between regions of interest
N Kasenburg, M Liptrot, KM Borgwardt, SN Ørting, M Nielsen, A Feragen
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Artikelen 1–20