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Tommy Löfstedt
Tommy Löfstedt
Associate Professor at Umeå University doing Machine Learning and Computer Vision in Medical Imaging
Verified email at umu.se
Title
Cited by
Cited by
Year
Gray-level invariant Haralick texture features
T Löfstedt, P Brynolfsson, T Asklund, T Nyholm, A Garpebring
PloS one 14 (2), e0212110, 2019
2262019
OnPLS—a novel multiblock method for the modelling of predictive and orthogonal variation
T Löfstedt, J Trygg
Journal of Chemometrics 25 (8), 441-455, 2011
1322011
Latent space manipulation for high-resolution medical image synthesis via the StyleGAN
L Fetty, M Bylund, P Kuess, G Heilemann, T Nyholm, D Georg, T Löfstedt
Zeitschrift für Medizinische Physik 30 (4), 305-314, 2020
782020
OnPLS integration of transcriptomic, proteomic and metabolomic data shows multi-level oxidative stress responses in the cambium of transgenic hipI-superoxide dismutase Populus …
V Srivastava, O Obudulu, J Bygdell, T Löfstedt, P Rydén, R Nilsson, ...
BMC genomics 14 (1), 893, 2013
752013
Transformer-based deep learning for predicting protein properties in the life sciences
A Chandra, L Tünnermann, T Löfstedt, R Gratz
eLife 12, e82819, 2023
732023
Understanding and interpreting machine learning in medical image computing applications
D Stoyanov, Z Taylor, SM Kia, I Oguz, M Reyes, A Martel, L Maier-Hein, ...
Springer International Publishing, 2018
602018
A Question-Centric Model for Visual Question Answering in Medical Imaging
MH Vu, T Löfstedt, T Nyholm, R Sznitman
IEEE transactions on medical imaging 39 (9), 2856-2868, 2020
562020
Global, local and unique decompositions in OnPLS for multiblock data analysis
T Löfstedt, D Hoffman, J Trygg
Analytica chimica acta 791, 13-24, 2013
512013
Evaluation of multislice inputs to convolutional neural networks for medical image segmentation
MH Vu, G Grimbergen, T Nyholm, T Löfstedt
Medical Physics 47 (12), 6216-6231, 2020
452020
QU-BraTS: MICCAI BraTS 2020 challenge on quantifying uncertainty in brain tumor segmentation-analysis of ranking scores and benchmarking results
R Mehta, A Filos, U Baid, C Sako, R McKinley, M Rebsamen, K Dätwyler, ...
The journal of machine learning for biomedical imaging 2022, 2022
432022
Investigating conditional GAN performance with different generator architectures, an ensemble model, and different MR scanners for MR-sCT conversion
L Fetty, T Löfstedt, G Heilemann, H Furtado, N Nesvacil, T Nyholm, ...
Physics in Medicine & Biology 65 (10), 105004, 2020
382020
TuNet: End-to-end hierarchical brain tumor segmentation using cascaded networks
MH Vu, T Nyholm, T Löfstedt
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2020
382020
Modelling human musculoskeletal functional movements using ultrasound imaging
M Peolsson, T Löfstedt, S Vogt, H Stenlund, A Arndt, J Trygg
BMC Medical Imaging 10 (1), 9, 2010
372010
Statistics and Machine Learning in Python
E Duchesnay, T Lofstedt, F Younes
352020
Identifying a neuroanatomical signature of schizophrenia, reproducible across sites and stages, using machine learning with structured sparsity
A de Pierrefeu, T Löfstedt, C Laidi, F Hadj‐Selem, J Bourgin, T Hajek, ...
Acta Psychiatrica Scandinavica, 2018
352018
A constrained singular value decomposition method that integrates sparsity and orthogonality
V Guillemot, D Beaton, A Gloaguen, T Löfstedt, B Levine, N Raymond, ...
PloS one 14 (3), e0211463, 2019
322019
Prediction of activation patterns preceding hallucinations in patients with schizophrenia using machine learning with structured sparsity
A de Pierrefeu, T Fovet, F Hadj‐Selem, T Löfstedt, P Ciuciu, S Lefebvre, ...
Human brain mapping 39 (4), 1777-1788, 2018
322018
Structured sparse principal components analysis with the TV-elastic net penalty
A de Pierrefeu, T Löfstedt, F Hadj-Selem, M Dubois, R Jardri, T Fovet, ...
IEEE transactions on medical imaging 37 (2), 396-407, 2018
292018
Ensemble of streamlined bilinear visual question answering models for the imageclef 2019 challenge in the medical domain
MH Vu, R Sznitman, T Nyholm, T Löfstedt
Working Notes of CLEF, 2019
242019
Predictive support recovery with TV-elastic net penalty and logistic regression: An application to structural MRI
M Dubois, F Hadj-Selem, T Löfstedt, M Perrot, C Fischer, V Frouin, ...
2014 International Workshop on Pattern Recognition in Neuroimaging, 1-4, 2014
242014
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Articles 1–20