Tommy Löfstedt

发表

COMPARISON OF GENERATIVE ADVERSARIAL NETWORKS IN MEDICAL IMAGING APPLICATIONS MR to CT image synthesis

Christoer Edlund, Tommy Löfstedt, 2019 .

A constrained singular value decomposition method that integrates sparsity and orthogonality

H. Abdi, A. Tenenhaus, V. Guillemot, 2019, PloS one.

Supplement to " An Iterative Smoothing Algorithm for Regression with Structured Sparsity "

E. Duchesnay, V. Frouin, V. Guillemot, 2016 .

Gray-level invariant Haralick texture features

Tommy Löfstedt, Patrik Brynolfsson, Tufve Nyholm, 2019, PloS one.

Fractal Geometry, Graph and Tree Constructions

Tommy Löfstedt, 2008 .

Evaluation of Multi-Slice Inputs to Convolutional Neural Networks for Medical Image Segmentation pdf

Tommy Löfstedt, Minh H. Vu, Tufve Nyholm, 2019, ArXiv.

Density estimation of grey-level co-occurrence matrices for image texture analysis

D. Georg, T. Helbich, Tommy Löfstedt, 2018, Physics in medicine and biology.

Identifying a neuroanatomical signature of schizophrenia, reproducible across sites and stages, using machine learning with structured sparsity

M. Leboyer, E. Duchesnay, P. Ciuciu, 2018, Acta psychiatrica Scandinavica.

Continuation of Nesterov's Smoothing for Regression with Structured Sparsity in High-Dimensional Neuroimaging

E. Duchesnay, V. Frouin, V. Guillemot, 2016, 1605.09658.

Reproducibility of the Methods in Medical Imaging with Deep Learning

J. Jonsson, Tommy Löfstedt, T. Nyholm, 2022, 2210.11146.

Transformer-based deep learning for predicting protein properties in the life sciences

Tommy Löfstedt, A. Chandra, Laura Tünnermann, 2023, eLife.

Continuation of Nesterov’s Smoothing for Regression With Structured Sparsity in High-Dimensional Neuroimaging

Tommy Löfstedt, Elvis Dohmatob, Vincent Guillemot, 2016, IEEE Transactions on Medical Imaging.

Predictive support recovery with TV-Elastic Net penalty and logistic regression: An application to structural MRI

Vincent Frouin, Clara Fischer, Tommy Löfstedt, 2014, 2014 International Workshop on Pattern Recognition in Neuroimaging.

OnPLS : Orthogonal projections to latent structures in multiblock and path model data analysis

Tommy Löfstedt, Tommy Löfstedt, 2012 .

Network Regularization in Imaging Genetics Improves Prediction Performances and Model Interpretability on Alzheimer’s Disease

N. Guigui, V. Guillemot, A. Gloaguen, 2019, 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019).

OnPLS integration of transcriptomic, proteomic and metabolomic data shows multi-level oxidative stress responses in the cambium of transgenic hipI- superoxide dismutase Populus plants

J. Trygg, T. Moritz, G. Wingsle, 2013, BMC Genomics.

Global, local and unique decompositions in OnPLS for multiblock data analysis.

Tommy Löfstedt, Johan Trygg, J. Trygg, 2013, Analytica chimica acta.

OnPLS path modelling

Tommy Löfstedt, Johan Trygg, Mohamed Hanafi, 2012 .

OnPLS—a novel multiblock method for the modelling of predictive and orthogonal variation

Tommy Löfstedt, Johan Trygg, J. Trygg, 2011 .

Bayesian non-linear regression with spatial priors for noise reduction and error estimation in quantitative MRI with an application in T1 estimation

Tommy Löfstedt, Mikael Bylund, Anders Garpebring, 2020, Physics in medicine and biology.

Simulated Data for Linear Regression with Structured and Sparse Penalties: Introducing pylearn-simulate

Tommy Löfstedt, Vincent Guillemot, Fouad Hadj-Selem, 2014, Journal of Statistical Software.

Investigating conditional GAN performance with different generator architectures, an ensemble model, and different MR scanners for MR-sCT conversion

Nicole Nesvacil, Tommy Löfstedt, Tufve Nyholm, 2020, Physics in medicine and biology.

A Question-Centric Model for Visual Question Answering in Medical Imaging

Raphael Sznitman, Tommy Löfstedt, Minh H. Vu, 2020, IEEE Transactions on Medical Imaging.

Latent Space Manipulation for High-Resolution Medical Image Synthesis via the StyleGAN.

Tommy Löfstedt, Tufve Nyholm, Lukas Fetty, 2020, Zeitschrift fur medizinische Physik.

Interpretable and stable prediction of schizophrenia on a large multisite dataset using machine learning with structured sparsity

Philippe Ciuciu, Tommy Löfstedt, Fouad Hadj-Selem, 2018, 2018 International Workshop on Pattern Recognition in Neuroimaging (PRNI).

Evaluation of Multi-Slice Inputs to Convolutional Neural Networks for Medical Image Segmentation

Minh H. Vu, Tommy Löfstedt, T. Nyholm, 2019, Medical physics.

End-to-End Cascaded U-Nets with a Localization Network for Kidney Tumor Segmentation pdf

Tommy Löfstedt, Minh H. Vu, Tufve Nyholm, 2019, ArXiv.

Prediction of activation patterns preceding hallucinations in patients with schizophrenia using machine learning with structured sparsity

Philippe Ciuciu, Tommy Löfstedt, Renaud Jardri, 2018, Human brain mapping.

Near infrared and skin impedance spectroscopy – a possible support in the diagnostic process of skin tumours in primary health care

Tommy Löfstedt, B. Lindholm-Sethson, I. Bodén, 2015, Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging.

LatentAugment: Data Augmentation via Guided Manipulation of GAN's Latent Space

Minh H. Vu, Tommy Löfstedt, P. Soda, 2023, ArXiv.

Structured Sparse Principal Components Analysis With the TV-Elastic Net Penalty

Vincent Frouin, Philippe Ciuciu, Tommy Löfstedt, 2016, IEEE Transactions on Medical Imaging.

Ensemble of Streamlined Bilinear Visual Question Answering Models for the ImageCLEF 2019 Challenge in the Medical Domain

Raphael Sznitman, Tommy Löfstedt, Minh H. Vu, 2019, CLEF.

Multi-Decoder Networks with Multi-Denoising Inputs for Tumor Segmentation pdf

Tommy Löfstedt, Minh H. Vu, Tufve Nyholm, 2020, BrainLes@MICCAI.

Denoising and uncertainty estimation in parameter mapping with approximate Bayesian deep image priors.

Tommy Löfstedt, A. Garpebring, Max Hellström, 2023, Magnetic resonance in medicine.

Dynamic ultrasound imaging—A multivariate approach for the analysis and comparison of time-dependent musculoskeletal movements

Tommy Löfstedt, Johan Trygg, Olof Ahnlund, 2012, BMC Medical Imaging.

Modelling human musculoskeletal functional movements using ultrasound imaging

Tommy Löfstedt, Johan Trygg, Anton Arndt, 2010, BMC Medical Imaging.

Structured Sparse Principal Components Analysis With the TV-Elastic Net Penalty

E. Duchesnay, P. Ciuciu, R. Jardri, 2016, IEEE Transactions on Medical Imaging.

Towards MR contrast independent synthetic CT generation.

J. Jonsson, Tommy Löfstedt, T. Nyholm, 2023, Zeitschrift fur medizinische Physik.

Identifying a neuroanatomical signature of schizophrenia, reproducible across sites and stages, using machine learning with structured sparsity

M. Leboyer, E. Duchesnay, P. Ciuciu, 2018, Acta psychiatrica Scandinavica.

Global, local and unique decompositions in OnPLS for multiblock data analysis.

J. Trygg, Tommy Löfstedt, D. Hoffman, 2013, Analytica chimica acta.

Safety-critical computer vision: an empirical survey of adversarial evasion attacks and defenses on computer vision systems

E. Elmroth, Tommy Löfstedt, Charles Meyers, 2023, Artificial Intelligence Review.

A Data-Adaptive Loss Function for Incomplete Data and Incremental Learning in Semantic Image Segmentation

Tommy Löfstedt, Minh H. Vu, Tufve Nyholm, 2021, IEEE Transactions on Medical Imaging.

Density estimation of grey-level co-occurrence matrices for image texture analysis

D. Georg, T. Helbich, Tommy Löfstedt, 2018, Physics in medicine and biology.

End-to-End Cascaded U-Nets with a Localization Network for Kidney Tumor Segmentation

Tommy Löfstedt, Minh H. Vu, Tufve Nyholm, 2019, Submissions to the 2019 Kidney Tumor Segmentation Challenge: KiTS19.