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Johannes Ulén
Johannes Ulén
Eigenvision AB
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Titel
Zitiert von
Zitiert von
Jahr
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
1322019
Hep-2 staining pattern classification
P Strandmark, J Ulén, F Kahl
International Conference on Pattern Recognition (ICPR), 33-36, 2012
932012
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
882020
In Defense of 3D-Label Stereo
C Olsson, J Ulén, Y Boykov
Conference on Computer Vision and Pattern Recognition (CVPR), 2013
832013
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
532020
Shortest Paths with Higher-Order Regularization
J Ulén, P Strandmark, F Kahl
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015
502015
An Efficient Optimization Framework for Multi-Region Segmentation based on Lagrangian Duality
J Ulén, P Strandmark, F Kahl
IEEE Transactions on Medical Imaging, 2013
492013
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
462021
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
332021
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
322019
AI-based detection of lung lesions in [18F]FDG PET-CT from lung cancer patients
P Borrelli, J Ly, R Kaboteh, J Ulén, O Enqvist, E Trägårdh, L Edenbrandt
EJNMMI physics 8, 1-11, 2021
292021
Shortest Paths with Curvature and Torsion
P Strandmark, J Ulén, F Kahl, L Grady
International Conference on Computer Vision (ICCV), 2013
262013
Auto-segmentations by convolutional neural network in cervical and anorectal cancer with clinical structure sets as the ground truth
H Sartor, D Minarik, O Enqvist, J Ulén, A Wittrup, M Bjurberg, E Trägårdh
Clinical and Translational Radiation Oncology 25, 37-45, 2020
242020
Automated quantification of reference levels in liver and mediastinal blood pool for the Deauville therapy response classification using FDG‐PET/CT in Hodgkin and non‐Hodgkin …
M Sadik, E Lind, E Polymeri, O Enqvist, J Ulén, E Trägårdh
Clinical physiology and functional imaging 39 (1), 78-84, 2019
242019
Freely Available, Fully Automated AI-Based Analysis of Primary Tumour and Metastases of Prostate Cancer in Whole-Body [18F]-PSMA-1007 PET-CT
E Trägårdh, O Enqvist, J Ulén, J Jögi, U Bitzén, F Hedeer, K Valind, ...
Diagnostics 12 (9), 2101, 2022
232022
Freely available artificial intelligence for pelvic lymph node metastases in PSMA PET-CT that performs on par with nuclear medicine physicians
E Trägårdh, O Enqvist, J Ulén, E Hvittfeldt, S Garpered, SL Belal, A Bjartell, ...
European Journal of Nuclear Medicine and Molecular Imaging 49 (10), 3412-3418, 2022
232022
Partial Enumeration and Curvature Regularization
C Olsson, J Ulén, Y Boykov, V Kolmogorov
International Conference on Computer Vision (ICCV), 2013
202013
Good Features for Reliable Registration in Multi-Atlas Segmentation.
F Kahl, J Alvén, O Enqvist, F Fejne, J Ulén, J Fredriksson, M Landgren, ...
VISCERAL Challenge@ ISBI, 12-17, 2015
192015
Application of an artificial intelligence-based tool in [18F]FDG PET/CT for the assessment of bone marrow involvement in multiple myeloma
C Sachpekidis, O Enqvist, J Ulén, A Kopp-Schneider, L Pan, A Jauch, ...
European Journal of Nuclear Medicine and Molecular Imaging 50 (12), 3697-3708, 2023
162023
Artificial intelligence could alert for focal skeleton/bone marrow uptake in Hodgkin’s lymphoma patients staged with FDG-PET/CT
M Sadik, J López-Urdaneta, J Ulén, O Enqvist, A Krupic, R Kumar, ...
Scientific Reports 11 (1), 10382, 2021
162021
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