Yi Ou Li

Summary

Affiliation: University of Maryland
Country: USA

Publications

  1. pmc Joint Blind Source Separation by Multi-set Canonical Correlation Analysis
    Yi Ou Li
    Y O Li, T Adali, and Wei Wang are with the Department of Computer Science and Electrical Engineering, University of Maryland Baltimore County, Baltimore, MD 21250 USA e mail
    IEEE Trans Signal Process 57:3918-3929. 2009
  2. pmc A feature-selective independent component analysis method for functional MRI
    Yi Ou Li
    Department of Computer Science and Electrical Engineering, University of Maryland Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA
    Int J Biomed Imaging 2007:15635. 2007
  3. ncbi request reprint Estimating the number of independent components for functional magnetic resonance imaging data
    Yi Ou Li
    Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County, Baltimore, Maryland 21250, USA
    Hum Brain Mapp 28:1251-66. 2007
  4. pmc Multi-set canonical correlation analysis for the fusion of concurrent single trial ERP and functional MRI
    Nicolle M Correa
    Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County, ITE 325 B, 1000 Hilltop Circle, Baltimore, MD 21250, USA
    Neuroimage 50:1438-45. 2010
  5. pmc Canonical Correlation Analysis for Feature-Based Fusion of Biomedical Imaging Modalities and Its Application to Detection of Associative Networks in Schizophrenia
    Nicolle M Correa
    Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County, Baltimore, MD 21250 USA e mail
    IEEE J Sel Top Signal Process 2:998-1007. 2008

Collaborators

Detail Information

Publications5

  1. pmc Joint Blind Source Separation by Multi-set Canonical Correlation Analysis
    Yi Ou Li
    Y O Li, T Adali, and Wei Wang are with the Department of Computer Science and Electrical Engineering, University of Maryland Baltimore County, Baltimore, MD 21250 USA e mail
    IEEE Trans Signal Process 57:3918-3929. 2009
    ..We apply M-CCA to analysis of functional magnetic resonance imaging (fMRI) data from multiple subjects and show its utility in estimating meaningful brain activations from a visuomotor task...
  2. pmc A feature-selective independent component analysis method for functional MRI
    Yi Ou Li
    Department of Computer Science and Electrical Engineering, University of Maryland Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA
    Int J Biomed Imaging 2007:15635. 2007
    ....
  3. ncbi request reprint Estimating the number of independent components for functional magnetic resonance imaging data
    Yi Ou Li
    Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County, Baltimore, Maryland 21250, USA
    Hum Brain Mapp 28:1251-66. 2007
    ....
  4. pmc Multi-set canonical correlation analysis for the fusion of concurrent single trial ERP and functional MRI
    Nicolle M Correa
    Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County, ITE 325 B, 1000 Hilltop Circle, Baltimore, MD 21250, USA
    Neuroimage 50:1438-45. 2010
    ....
  5. pmc Canonical Correlation Analysis for Feature-Based Fusion of Biomedical Imaging Modalities and Its Application to Detection of Associative Networks in Schizophrenia
    Nicolle M Correa
    Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County, Baltimore, MD 21250 USA e mail
    IEEE J Sel Top Signal Process 2:998-1007. 2008
    ..Additionally, we compare our scheme with an independent component analysis based fusion method, joint-ICA that has proven useful for such a study and note that the two methods provide complementary perspectives on data fusion...