• DocumentCode
    4533
  • Title

    Spatially Sparse, Temporally Smooth MEG Via Vector \\ell _{0}

  • Author

    Cassidy, Ben ; Solo, Victor

  • Author_Institution
    Sch. of Electr. Eng., Univ. of New South Wales, Sydney, NSW, Australia
  • Volume
    34
  • Issue
    6
  • fYear
    2015
  • fDate
    Jun-15
  • Firstpage
    1282
  • Lastpage
    1293
  • Abstract
    In this paper, we describe a new method for solving the magnetoencephalography inverse problem: temporal vector ℓ0-penalized least squares (TV-L0LS). The method calculates maximally sparse current dipole magnitudes and directions via spatial ℓ0 regularization on a cortically-distributed source grid, while constraining the solution to be smooth with respect to time. We demonstrate the utility of this method on real and simulated data by comparison to existing methods.
  • Keywords
    inverse problems; least squares approximations; magnetoencephalography; medical signal processing; cortically-distributed source grid; inverse problem; magnetoencephalography; maximally sparse current dipole magnitudes; spatial ℓ0 regularization; spatially sparse temporally smooth MEG; temporal vector ℓ0-penalized least squares; Brain modeling; Data models; Inverse problems; Sensor phenomena and characterization; Tuning; Vectors; Biomedical imaging; encephalography; optimization; sparsity;
  • fLanguage
    English
  • Journal_Title
    Medical Imaging, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0062
  • Type

    jour

  • DOI
    10.1109/TMI.2014.2383376
  • Filename
    7001685
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=4533