| Gray-level invariant Haralick texture features T Löfstedt, P Brynolfsson, T Asklund, T Nyholm, A Garpebring PloS one 14 (2), e0212110, 2019 | 235 | 2019 |
| 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 | 133 | 2011 |
| Transformer-based deep learning for predicting protein properties in the life sciences A Chandra, L Tünnermann, T Löfstedt, R Gratz eLife 12, e82819, 2023 | 86 | 2023 |
| 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 | 80 | 2020 |
| 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 | 76 | 2013 |
| 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 | 62 | 2018 |
| 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 | 58 | 2020 |
| Global, local and unique decompositions in OnPLS for multiblock data analysis T Löfstedt, D Hoffman, J Trygg Analytica chimica acta 791, 13-24, 2013 | 53 | 2013 |
| 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 | 47 | 2020 |
| 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 | 45 | 2022 |
| 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 | 39 | 2020 |
| 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 | 39 | 2020 |
| 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 | 37 | 2010 |
| Statistics and Machine Learning in Python E Duchesnay, T Lofstedt, F Younes | 36 | 2020 |
| 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 | 35 | 2018 |
| 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 | 33 | 2019 |
| 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 | 32 | 2018 |
| 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 | 29 | 2018 |
| 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 | 25 | 2019 |
| 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 | 24 | 2014 |
