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 *

211 related articles for article (PubMed ID: 30654748)

  • 1. Temporally constrained ICA with threshold and its application to fMRI data.
    Long Z; Wang Z; Zhang J; Zhao X; Yao L
    BMC Med Imaging; 2019 Jan; 19(1):6. PubMed ID: 30654748
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Temporally and spatially constrained ICA of fMRI data analysis.
    Wang Z; Xia M; Jin Z; Yao L; Long Z
    PLoS One; 2014; 9(4):e94211. PubMed ID: 24727944
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Improved FastICA algorithm in fMRI data analysis using the sparsity property of the sources.
    Ge R; Wang Y; Zhang J; Yao L; Zhang H; Long Z
    J Neurosci Methods; 2016 Apr; 263():103-14. PubMed ID: 26880161
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Analysis of fMRI data by blind separation into independent spatial components.
    McKeown MJ; Makeig S; Brown GG; Jung TP; Kindermann SS; Bell AJ; Sejnowski TJ
    Hum Brain Mapp; 1998; 6(3):160-88. PubMed ID: 9673671
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A semi-blind online dictionary learning approach for fMRI data.
    Long Z; Liu L; Gao Z; Chen M; Yao L
    J Neurosci Methods; 2019 Jul; 323():1-12. PubMed ID: 31085215
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Semiblind spatial ICA of fMRI using spatial constraints.
    Lin QH; Liu J; Zheng YR; Liang H; Calhoun VD
    Hum Brain Mapp; 2010 Jul; 31(7):1076-88. PubMed ID: 20017117
    [TBL] [Abstract][Full Text] [Related]  

  • 7. SCTICA: Sub-packet constrained temporal ICA method for fMRI data analysis.
    Shi Y; Zeng W
    Comput Biol Med; 2018 Nov; 102():75-85. PubMed ID: 30248514
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Tensor clustering on outer-product of coefficient and component matrices of independent component analysis for reliable functional magnetic resonance imaging data decomposition.
    Hu G; Zhang Q; Waters AB; Li H; Zhang C; Wu J; Cong F; Nickerson LD
    J Neurosci Methods; 2019 Sep; 325():108359. PubMed ID: 31306718
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Separating 4D multi-task fMRI data of multiple subjects by independent component analysis with projection.
    Long Z; Li R; Wen X; Jin Z; Chen K; Yao L
    Magn Reson Imaging; 2013 Jan; 31(1):60-74. PubMed ID: 22898701
    [TBL] [Abstract][Full Text] [Related]  

  • 10. General nonunitary constrained ICA and its application to complex-valued fMRI data.
    Rodriguez PA; Anderson M; Calhoun VD; Adali T
    IEEE Trans Biomed Eng; 2015 Mar; 62(3):922-9. PubMed ID: 25420255
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A two-step super-Gaussian independent component analysis approach for fMRI data.
    Ge R; Yao L; Zhang H; Long Z
    Neuroimage; 2015 Sep; 118():344-58. PubMed ID: 26057592
    [TBL] [Abstract][Full Text] [Related]  

  • 12. An evaluation of independent component analyses with an application to resting-state fMRI.
    Risk BB; Matteson DS; Ruppert D; Eloyan A; Caffo BS
    Biometrics; 2014 Mar; 70(1):224-36. PubMed ID: 24350655
    [TBL] [Abstract][Full Text] [Related]  

  • 13. WASICA: An effective wavelet-shrinkage based ICA model for brain fMRI data analysis.
    Wang N; Zeng W; Shi Y; Ren T; Jing Y; Yin J; Yang J
    J Neurosci Methods; 2015 May; 246():75-96. PubMed ID: 25791013
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Spatial and temporal independent component analysis of functional MRI data containing a pair of task-related waveforms.
    Calhoun VD; Adali T; Pearlson GD; Pekar JJ
    Hum Brain Mapp; 2001 May; 13(1):43-53. PubMed ID: 11284046
    [TBL] [Abstract][Full Text] [Related]  

  • 15. [Blind source separation for fMRI signals using a new independent component analysis algorithm and principal component analysis].
    Zhang W; Shi Z; Tang H; Tang Y
    Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2007 Apr; 24(2):430-3. PubMed ID: 17591275
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Analysis of Residual Dependencies of Independent Components Extracted from fMRI Data.
    Vanello N; Ricciardi E; Landini L
    Comput Intell Neurosci; 2016; 2016():2961727. PubMed ID: 26839530
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Performance of blind source separation algorithms for fMRI analysis using a group ICA method.
    Correa N; Adali T; Calhoun VD
    Magn Reson Imaging; 2007 Jun; 25(5):684-94. PubMed ID: 17540281
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A New Constrained Spatiotemporal ICA Method Based on Multi-Objective Optimization for fMRI Data Analysis.
    Shi Y; Zeng W; Wang N; Zhao L
    IEEE Trans Neural Syst Rehabil Eng; 2018 Sep; 26(9):1690-1699. PubMed ID: 30028710
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Semi-blind ICA of fMRI: A method for utilizing hypothesis-derived time courses in a spatial ICA analysis.
    Calhoun VD; Adali T; Stevens MC; Kiehl KA; Pekar JJ
    Neuroimage; 2005 Apr; 25(2):527-38. PubMed ID: 15784432
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Improved estimation of the number of independent components for functional magnetic resonance data by a whitening filter.
    Hui M; Li R; Chen K; Jin Z; Yao L; Long Z
    IEEE J Biomed Health Inform; 2013 May; 17(3):629-41. PubMed ID: 24592464
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.