Motion estimated and compensated compressed sensing dynamic magnetic resonance imaging: What we can learn from video compression techniques

  • Authors:

  • Hong Jung;Jong Chul Ye

  • Affiliations:

  • Bio-Imaging and Signal Processing Laboratory, Department Bio-Brain Engineering, Korea Advanced Institute of Science & Technology (KAIST), Daejon 305-701, Republic of Korea;Bio-Imaging and Signal Processing Laboratory, Department Bio-Brain Engineering, Korea Advanced Institute of Science & Technology (KAIST), Daejon 305-701, Republic of Korea

  • Venue:
  • International Journal of Imaging Systems and Technology
  • Year:
  • 2010

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Abstract

Compressed sensing has become an extensive research area in MR community because of the opportunity for unprecedented high spatio-temporal resolution reconstruction. Because dynamic magnetic resonance imaging (MRI) usually has huge redundancy along temporal direction, compressed sensing theory can be effectively used for this application. Historically, exploiting the temporal redundancy has been the main research topics in video compression technique. This article compares the similarity and differences of compressed sensing dynamic MRI and video compression and discusses what MR can learn from the history of video compression research. In particular, we demonstrate that the motion estimation and compensation in video compression technique can be also a powerful tool to reduce the sampling requirement in dynamic MRI. Theoretical derivation and experimental results are presented to support our view. © 2010 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 20, 81–98, 2010