Parallel magnetic resonance imaging using compressed sensing

Ali Bilgin, Yookyung Kim, Hariharan G. Lalgudi, Theodore P. Trouard, Maria I. Altbach

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations


Although magnetic resonance imaging (MRI) is routinely used in clinical practice, long acquisition times limit its practical utility in many applications. To increase the data acquisition speed of MRI, parallel MRI (pMRI) techniques have recently been proposed. These techniques utilize multi-channel receiver arrays and are based on simultaneous acquisition of data from multiple receiver coils. Recently, a novel framework called Compressed Sensing (CS) was introduced. Since this new framework illustrates how signals can be reconstructed from much fewer samples than suggested by the Nyquist theory, it has the potential to significantly accelerate data acquisition in MRI. This paper illustrates that CS and pMRI techniques can be combined and such joint processing yields results that are superior to those obtained from independent utilization of each technique.

Original languageEnglish (US)
Title of host publicationApplications of Digital Image Processing XXXI
StatePublished - 2008
EventApplications of Digital Image Processing XXXI - San Diego, CA, United States
Duration: Aug 11 2008Aug 14 2008

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X


OtherApplications of Digital Image Processing XXXI
Country/TerritoryUnited States
CitySan Diego, CA


  • Compressed sensing
  • Compressive sampling
  • Magnetic resonance imaging
  • Parallel imaging

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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