ArticleIEEE transactions on medical imaging2016
The Iterative Reweighted Mixed-Norm Estimate for Spatio-Temporal MEG/EEG Source Reconstruction.
Article in IEEE transactions on medical imaging, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Multiorientation Simultaneous Computation of Back-Projection CT Image Reconstruction Algorithm in Staging Diagnosis of Bladder Cancer.Computational and mathematical methods in medicine · 2022Trial
- Efficient Super-Resolution Bayesian Eletromagnetic Brain Imaging.IEEE transactions on bio-medical engineering · 2026Article
- EEG dynamic source imaging using a regularized optimization with spatio-temporal constraints.Medical & biological engineering & computing · 2024Article
- Improving source estimation of retinotopic MEG responses by combining data from multiple subjects.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- An F-ratio-based method for estimating the number of active sources in MEG.Frontiers in human neuroscience · 2023Article
- Sparse algorithms for EEG source localization.Medical & biological engineering & computing · 2021Review
- Unification of sparse Bayesian learning algorithms for electromagnetic brain imaging with the majorization minimization framework.NeuroImage · 2021Article
- EEG Signal Reconstruction Using a Generative Adversarial Network With Wasserstein Distance and Temporal-Spatial-Frequency Loss.Frontiers in neuroinformatics · 2020Article
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Authors and funding
4 authors.
Funding
Abstract
Source imaging based on magnetoencephalography (MEG) and electroencephalography (EEG) allows for the non-invasive analysis of brain activity with high temporal and good spatial resolution. As the bioelectromagnetic inverse problem is ill-posed, constraints are required. For the analysis of evoked brain activity, spatial sparsity of the neuronal activation is a common assumption. It is often taken into account using convex constraints based on the l
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