• DocumentCode
    1508171
  • Title

    Guest Editorial Compressive Sensing for Biomedical Imaging

  • Author

    Ge Wang ; Bresler, Yoram ; Ntziachristos, Vasilis

  • Author_Institution
    VT-WFU Sch. of Biomed. Eng. & Sci., Virginia Tech, Blacksburg, VA, USA
  • Volume
    30
  • Issue
    5
  • fYear
    2011
  • fDate
    5/1/2011 12:00:00 AM
  • Firstpage
    1013
  • Lastpage
    1016
  • Abstract
    Compressive sensing (CS) has seen impressive successes and fast growth over the past ten years, including applications in medical imaging. Applications of CS to magnetic resonance imaging (MRI) have been the earliest, most numerous, and most diverse, owing to the tremendous flexibility in designing the acquisition process and the pressing need that MRI has, as a slow acquisition modality, to reduce the sampling requirements.
  • Keywords
    biomedical MRI; data compression; image coding; medical image processing; L1-norm minimization; biomedical imaging; compressive sensing; data acquisition process; greedy algorithms; image compression; optimization procedure; uncompressed image; Compressed sensing; Special issues and sections;
  • fLanguage
    English
  • Journal_Title
    Medical Imaging, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0062
  • Type

    jour

  • DOI
    10.1109/TMI.2011.2145070
  • Filename
    5760046