These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

208 related articles for article (PubMed ID: 23291276)

  • 1. Time-frequency mixed-norm estimates: sparse M/EEG imaging with non-stationary source activations.
    Gramfort A; Strohmeier D; Haueisen J; Hämäläinen MS; Kowalski M
    Neuroimage; 2013 Apr; 70():410-22. PubMed ID: 23291276
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Functional brain imaging with M/EEG using structured sparsity in time-frequency dictionaries.
    Gramfort A; Strohmeier D; Haueisen J; Hamalainen M; Kowalski M
    Inf Process Med Imaging; 2011; 22():600-11. PubMed ID: 21761689
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Mixed-norm estimates for the M/EEG inverse problem using accelerated gradient methods.
    Gramfort A; Kowalski M; Hämäläinen M
    Phys Med Biol; 2012 Apr; 57(7):1937-61. PubMed ID: 22421459
    [TBL] [Abstract][Full Text] [Related]  

  • 4. The Iterative Reweighted Mixed-Norm Estimate for Spatio-Temporal MEG/EEG Source Reconstruction.
    Strohmeier D; Bekhti Y; Haueisen J; Gramfort A
    IEEE Trans Med Imaging; 2016 Oct; 35(10):2218-2228. PubMed ID: 27093548
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Multi-subject MEG/EEG source imaging with sparse multi-task regression.
    Janati H; Bazeille T; Thirion B; Cuturi M; Gramfort A
    Neuroimage; 2020 Oct; 220():116847. PubMed ID: 32438046
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Localization Estimation Algorithm (LEA): a supervised prior-based approach for solving the EEG/MEG inverse problem.
    Mattout J; Pélégrini-Issac M; Bellio A; Daunizeau J; Benali H
    Inf Process Med Imaging; 2003 Jul; 18():536-47. PubMed ID: 15344486
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Modified covariance beamformer for solving MEG inverse problem in the environment with correlated sources.
    Kuznetsova A; Nurislamova Y; Ossadtchi A
    Neuroimage; 2021 Mar; 228():117677. PubMed ID: 33385549
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Automated model selection in covariance estimation and spatial whitening of MEG and EEG signals.
    Engemann DA; Gramfort A
    Neuroimage; 2015 Mar; 108():328-42. PubMed ID: 25541187
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A distributed spatio-temporal EEG/MEG inverse solver.
    Ou W; Hämäläinen MS; Golland P
    Neuroimage; 2009 Feb; 44(3):932-46. PubMed ID: 18603008
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A distributed spatio-temporal EEG/MEG inverse solver.
    Ou W; Golland P; Hämäläinen M
    Med Image Comput Comput Assist Interv; 2008; 11(Pt 1):26-34. PubMed ID: 18979728
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Spatial fidelity of MEG/EEG source estimates: A general evaluation approach.
    Samuelsson JG; Peled N; Mamashli F; Ahveninen J; Hämäläinen MS
    Neuroimage; 2021 Jan; 224():117430. PubMed ID: 33038537
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Estimation of neural dynamics from MEG/EEG cortical current density maps: application to the reconstruction of large-scale cortical synchrony.
    David O; Garnero L; Cosmelli D; Varela FJ
    IEEE Trans Biomed Eng; 2002 Sep; 49(9):975-87. PubMed ID: 12214887
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Towards an objective evaluation of EEG/MEG source estimation methods - The linear approach.
    Hauk O; Stenroos M; Treder MS
    Neuroimage; 2022 Jul; 255():119177. PubMed ID: 35390459
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Spatially sparse source cluster modeling by compressive neuromagnetic tomography.
    Chang WT; Nummenmaa A; Hsieh JC; Lin FH
    Neuroimage; 2010 Oct; 53(1):146-60. PubMed ID: 20488248
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Solving the EEG inverse problem based on space-time-frequency structured sparsity constraints.
    Castaño-Candamil S; Höhne J; Martínez-Vargas JD; An XW; Castellanos-Domínguez G; Haufe S
    Neuroimage; 2015 Sep; 118():598-612. PubMed ID: 26048621
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Assessment of subcortical source localization using deep brain activity imaging model with minimum norm operators: a MEG study.
    Attal Y; Schwartz D
    PLoS One; 2013; 8(3):e59856. PubMed ID: 23527277
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Source reconstruction of brain electromagnetic fields--source iteration of minimum norm (SIMN).
    Liang WK; Wang MS
    Neuroimage; 2009 Oct; 47(4):1301-11. PubMed ID: 19361564
    [TBL] [Abstract][Full Text] [Related]  

  • 18. MEG source imaging method using fast L1 minimum-norm and its applications to signals with brain noise and human resting-state source amplitude images.
    Huang MX; Huang CW; Robb A; Angeles A; Nichols SL; Baker DG; Song T; Harrington DL; Theilmann RJ; Srinivasan R; Heister D; Diwakar M; Canive JM; Edgar JC; Chen YH; Ji Z; Shen M; El-Gabalawy F; Levy M; McLay R; Webb-Murphy J; Liu TT; Drake A; Lee RR
    Neuroimage; 2014 Jan; 84():585-604. PubMed ID: 24055704
    [TBL] [Abstract][Full Text] [Related]  

  • 19. The impact of MEG source reconstruction method on source-space connectivity estimation: A comparison between minimum-norm solution and beamforming.
    Hincapié AS; Kujala J; Mattout J; Pascarella A; Daligault S; Delpuech C; Mery D; Cosmelli D; Jerbi K
    Neuroimage; 2017 Aug; 156():29-42. PubMed ID: 28479475
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Bayesian Algorithm Based Localization of EEG Recorded Electromagnetic Brain Activity.
    Jatoi MA; Kamel N; Musavi SHA; López JD
    Curr Med Imaging Rev; 2019; 15(2):184-193. PubMed ID: 31975664
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.