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Staff photo Tommy Löfstedt

Tommy Löfstedt

Docent and associate professor in computing science. Doing research in machine learning and computer vision, often with applications in medical image analysis or the life sciences.

Research qualifications: Docent

Contact

E-mail
tommy.lofstedt@umu.se
Phone

Works at

Affiliation
Associate professor at Department of Computing Science
Location
MIT-huset, Umeå universitet, MIT.E.252 Umeå universitet, 901 87 Umeå
Affiliation
Affiliated as other position at Department of Mathematics and Mathematical Statistics
Location
MIT-huset, plan 3, Matematik och matematisk statistik Umeå universitet, 901 87 Umeå

Much of the recent successes within the field of artificial intelligence (AI) in the last 10-15 years can be attributed to a subarea of AI called machine learning. I am a researcher in machine learning and computer vision, often with applications in medical image analysis. Much of my research is developing novel methods for automatic segmentation, and to develop novel regularisation methods for machine learning to, among other things, improve the possibilities to interpret the results.

We are currently looking for a post-doctoral researcher in generative modelling in machine learning:

We are currently offering master's thesis projects in the following areas:

  • Medical image segmentation
  • Reinforcement learning
Using the Krylov subspace formulation to improve regularisation and interpretation in partial least squares regression
Computational statistics (Zeitschrift)
Löfstedt, Tommy
Massively parallel evasion attacks and the pitfalls of adversarial retraining
EAI Endorsed Transactions on Internet of Things, Gent EAI 2024, Vol. 10
Meyers, Charles; Löfstedt, Tommy; Elmroth, Erik
Towards MR contrast independent synthetic CT generation
Zeitschrift für Medizinische Physik, Elsevier 2024, Vol. 34, (2) : 270-277
Simkó, Attila; Bylund, Mikael; Jönsson, Gustav; et al.
Transformer-based deep learning for predicting protein properties in the life sciences
eLIFE, eLife Sciences Publications 2023, Vol. 12
Chandra, Abel; Tünnermann, Laura; Löfstedt, Tommy; et al.
Denoising and uncertainty estimation in parameter mapping with approximate Bayesian deep image priors
Magnetic Resonance in Medicine, John Wiley & Sons 2023, Vol. 90, (6) : 2557-2571
Hellström, Max; Löfstedt, Tommy; Garpebring, Anders
Safety-critical computer vision: an empirical survey of adversarial evasion attacks and defenses on computer vision systems
Artificial Intelligence Review, Elsevier 2023, Vol. 56 : 217-251
Meyers, Charles; Löfstedt, Tommy; Elmroth, Erik
Reproducibility of the methods in medical imaging with deep learning
Medical imaging with deep learning 2023, ML Research Press 2023 : 95-106
Simkó, Attila; Garpebring, Anders; Jonsson, Joakim; et al.
Improving MR image quality with a multi-task model, using convolutional losses
BMC Medical Imaging, BioMed Central (BMC) 2023, Vol. 23, (1)
Simkó, Attila; Ruiter, Simone; Löfstedt, Tommy; et al.
QU-BraTS: MICCAI BraTS 2020 Challenge on QuantifyingUncertainty in Brain Tumor Segmentation - Analysis of Ranking Scores and Benchmarking Results
Journal of Machine Learning for Biomedical Imaging : 1-54
Mehta, Raghav; Filos, Angelos; Baid, Ujjwal; et al.
MRI bias field correction with an implicitly trained CNN
Proceedings of the 5th international conference on medical imaging with deep learning, ML Research Press 2022 : 1125-1138
Simkó, Attila; Löfstedt, Tommy; Garpebring, Anders; et al.
A Data-Adaptive Loss Function for Incomplete Data and Incremental Learning in Semantic Image Segmentation
IEEE Transactions on Medical Imaging, IEEE 2022, Vol. 41, (6) : 1320-1330
Vu, Minh Hoang; Norman, Gabriella; Nyholm, Tufve; et al.
Changing the Contrast of Magnetic Resonance Imaging Signals using Deep Learning
Proceedings of the Fourth Conference on Medical Imaging with Deep Learning, PMLR, Lübeck University; Hamburg University of Technology 2021 : 713-727
Simkó, Attila; Löfstedt, Tommy; Garpebring, Anders; et al.
Multi-decoder Networks with Multi-denoising Inputs for Tumor Segmentation
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, Springer 2021 : 412-423
Vu, Minh Hoang; Nyholm, Tufve; Löfstedt, Tommy
Latent space manipulation for high-resolution medical image synthesis via the StyleGAN
Zeitschrift für Medizinische Physik, Elsevier 2020, Vol. 30, (4) : 305-314
Fetty, Lukas; Bylund, Mikael; Kuess, Peter; et al.
Investigating conditional GAN performance with different generator architectures, an ensemble model, and different MR scanners for MR-sCT conversion
Physics in Medicine and Biology, Institute of Physics Publishing (IOPP) 2020, Vol. 65, (10)
Fetty, Lukas; Löfstedt, Tommy; Heilemann, Gerd; et al.
Bayesian non-linear regression with spatial priors for noise reduction and error estimation in quantitative MRI with an application in T1 estimation
Physics in Medicine and Biology, Institute of Physics (IOP) 2020, Vol. 65, (22)
Löfstedt, Tommy; Hellström, Max; Bylund, Mikael; et al.
Evaluation of multislice inputs to convolutional neural networks for medical image segmentation
Medical physics (Lancaster), John Wiley & Sons 2020, Vol. 47, (12) : 6216-6231
Vu, Minh H.; Grimbergen, Guus; Nyholm, Tufve; et al.
A Question-Centric Model for Visual Question Answering in Medical Imaging
IEEE Transactions on Medical Imaging, IEEE 2020, Vol. 39, (9) : 2856-2868
Vu, Minh Hoang; Löfstedt, Tommy; Nyholm, Tufve; et al.
TuNet: End-to-End Hierarchical Brain Tumor Segmentation Using Cascaded Networks
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries: 5th International Workshop, BrainLes 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Revised Selected Papers, Part I, Cham: Springer 2020 : 174-186
Vu, Minh Hoang; Nyholm, Tufve; Löfstedt, Tommy
Network Regularization in Imaging Genetics Improves Prediction Performances and Model Interpretability on Alzheimer’s Disease
2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019), IEEE 2019 : 1403-1406
Guigui, N.; Philippe, C.; Gloaguen, A.; et al.
A constrained singular value decomposition method that integrates sparsity and orthogonality
PLOS ONE, Vol. 14, (3)
Guillemot, Vincent; Beaton, Derek; Gloaguen, Arnaud; et al.
Gray-level invariant Haralick texture features
PLOS ONE, Public Library of Science 2019, Vol. 14, (2)
Löfstedt, Tommy; Brynolfsson, Patrik; Nyholm, Tufve; et al.
Localization Network and End-to-End Cascaded U-Nets for Kidney Tumor Segmentation
MICCAI 2019, Shenzhen, China, Oct 13-17, 2019
Vu, Minh; Grimbergen, Guus; Simkó, Attila; et al.
Ensemble of Streamlined Bilinear Visual Question Answering Models for the ImageCLEF 2019 Challenge in the Medical Domain
CLEF 2019: Working Notes of CLEF 2019 - Conference and Labs of the Evaluation Forum
Vu, Minh Hoang; Sznitman, Raphael; Nyholm, Tufve; et al.
Gray-level invariant Haralick texture features
Radiotherapy and Oncology, Elsevier 2018, Vol. 127 : S279-S280
Brynolfsson, Patrik; Löfstedt, Tommy; Asklund, Thomas; et al.
Using deep learning to generate synthetic CTs for radiotherapy treatment planning
Radiotherapy and Oncology, Elsevier 2018, Vol. 127 : S283-S283
Bylund, Mikael; Jonsson, Joakim; Lundman, Josef; et al.
Prediction of activation patterns preceding hallucinations in patients with schizophrenia using machine learning with structured sparsity
Human Brain Mapping, Vol. 39, (4) : 1777-1788
de Pierrefeu, Amicie; Fovet, Thomas; Hadj-Selem, Fouad; et al.
Structured Sparse Principal Components Analysis With the TV-Elastic Net Penalty
IEEE Transactions on Medical Imaging, IEEE 2018, Vol. 37, (2) : 396-407
de Pierrefeu, Amicie; Löfstedt, Tommy; Hadj-Selem, Fouad; et al.
Identifying a neuroanatomical signature of schizophrenia, reproducible across sites and stages, using machine-learning with structured sparsity
Acta Psychiatrica Scandinavica, John Wiley & Sons 2018, Vol. 138 : 571-580
de Pierrefeu, Amicie; Löfstedt, Tommy; Laidi, C.; et al.
Interpretable and stable prediction of schizophrenia on a large multisite dataset using machine learning with structured sparsity
2018 International Workshop on Pattern Recognition in Neuroimaging (PRNI)
De Pierrefeu, Amicie; Löfstedt, Tommy; Laidi, Charles; et al.
Density Estimation of Grey-Level Co-Occurrence Matrices for Image Texture Analysis
Physics in Medicine and Biology, Institute of Physics and Engineering in Medicine 2018, Vol. 63, (19) : 9-15
Garpebring, Anders; Brynolfsson, Patrik; Kuess, Peter; et al.
Parameter estimation using weighted total least squares in the two-compartment exchange model
Magnetic Resonance in Medicine, John Wiley & Sons 2018, Vol. 79, (1) : 561-567
Garpebring, Anders; Tommy, Löfstedt
Continuation of Nesterov's Smoothing for Regression With Structured Sparsity in High-Dimensional Neuroimaging
IEEE Transactions on Medical Imaging, IEEE 2018, Vol. 37, (11) : 2403-2413
Hadj-Selem, Fouad; Löfstedt, Tommy; Dohmatob, Elvis; et al.
MLCN 2018 preface
Understanding and interpreting machine learning in medical image computing applications: First International Workshops MLCN 2018, DLF 2018, and iMIMIC 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16-20, 2018, Proceedings
Kia, Seyed Mostafa; Marquand, Andre; Duchesnay, Edouard; et al.
Simulated Data for Linear Regression with Structured and Sparse Penalties: Introducing pylearn-simulate
Journal of Statistical Software, Foundation for Open Access Statistics 2018, Vol. 87, (3)
Löfstedt, Tommy; Guillemot, Vincent; Frouin, Vincent; et al.
Structured Variable Selection for Regularized Generalized Canonical Correlation Analysis
MULTIPLE FACETS OF PARTIAL LEAST SQUARES AND RELATED METHODS, SPRINGER INT PUBLISHING AG 2016 : 129-139
Löfstedt, Tommy; Hadj-Selem, Fouad; Guillemot, Vincent; et al.
Near infrared and skin impedance spectroscopy: a possible support in the diagnostic process of skin tumours in primary health care
Skin research and technology, John Wiley & Sons 2015, Vol. 21, (4) : 493-499
Hägerlind, E.; Falk, M.; Löfstedt, Tommy; et al.
Preliminary evaluation of dorsal muscle activity during resisted cervical extension in patients with longstanding pain and disability following anterior cervical decompression and fusion surgery
Physiotherapy, Vol. 101, (1) : 69-74
Peolsson, A.; Peolsson, Michael; Jull, G.; et al.
Predictive support recovery with TV-Elastic Net penalty and logistic regression: An application to structural MRI
IEEE conference proceedings 2014
Dubois, Mathieu; Hadj-Selem, Fouad; Löfstedt, Tommy; et al.
Multiblock and Path Modeling with OnPLS
New Perspectives in Partial Least Squares and Related Methods (Part IV), Springer Science+Business Media B.V. 2013 : 209-220
Löfstedt, Tommy; Hanafi, Mohamed; Trygg, Johan
Global, local and unique decompositions in OnPLS for multiblock data analysis
Analytica Chimica Acta, Vol. 791 : 13-24
Löfstedt, Tommy; Hoffman, Daniel; Trygg, Johan
OnPLS integration of transcriptomic, proteomic and metabolomic data shows multi-level oxidative stress responses in the cambium of transgenic hipI- superoxide dismutase Populus plants
BMC Genomics, BioMed Central 2013, Vol. 14
Srivastava, Vaibhav; Obudulu, Ogonna; Bygdell, Joakim; et al.
OnPLS: Orthogonal projections to latent structures in multiblock and path model data analysis
Umeå: Umeå universitet 2012
Löfstedt, Tommy
Dynamic ultrasound imaging: a multivariate approach for the analysis and comparison of time-dependent musculoskeletal movements
BMC Medical Imaging, Vol. 12, (1) : 29-
Löfstedt, Tommy; Ahnlund, Olof; Peolsson, Michael; et al.
Bi-modal OnPLS
Journal of Chemometrics, John Wiley & Sons 2012, Vol. 26, (6) : 236-245
Löfstedt, Tommy; Eriksson, Lennart; Gunilla Wormbs, Gunilla; et al.
OnPLS path modelling
Chemometrics and Intelligent Laboratory Systems, Elsevier 2012, Vol. 118 : 139-149
Löfstedt, Tommy; Hanafi, Mohamed; Mazerolles, Gérard; et al.
Ultrasound imaging with speckle tracking of cervical muscle deformation and deformation rate: isometric contraction of patients after anterior cervical decompression and fusion for cervical disc disease and controls
Manual Therapy, Vol. 17, (6) : 519-525
Peolsson, Anneli; Löfstedt, Tommy; Trygg, Johan; et al.
OnPLS—a novel multiblock method for the modelling of predictive and orthogonal variation
Journal of Chemometrics, John Wiley & Sons 2011, Vol. 25, (8) : 441-455
Löfstedt, Tommy; Trygg, Johan
Modelling human musculoskeletal functional movements using ultrasound imaging
BMC Medical Imaging, Vol. 10, (9)
Peolsson, Michael; Löfstedt, Tommy; Vogt, Susanna; et al.
Compressing the activation maps in deep convolutional neural networks and the regularization effect of compression
Vu, Minh H.; Garpebring, Anders; Nyholm, Tufve; et al.
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