• DocumentCode
    1817777
  • Title

    Highly accelerated parallel imaging methods for localized massive array coils: comparison using 64-channel phased-array data

  • Author

    Ji, Jim X. ; Son, Jong Bum ; McDougall, Mary P. ; Wright, Steve M.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Texas A&M Univ., TX
  • fYear
    2006
  • fDate
    6-9 April 2006
  • Firstpage
    734
  • Lastpage
    737
  • Abstract
    Massive parallel phased-array systems with 32, 64, or more receive channels have potential to achieve high scan time saving for parallel MRI. In the past decade, a number of parallel MRI methods have been proposed including SENSE, SMASH, PILS, GRAPPA, SPACE-RIP, SEA, and other methods. In this work, we investigate the optimality of four reconstruction methods for parallel imaging with massive localized linear phased-array coils. In particular, the artifact power, SNR, and scan efficiency of different methods are systematically compared and analyzed. The studies are based on real MR data collected using a 64-channel system for 2-D MR imaging. The results show that the auto-PILS method and the improved GRAPPA method provide the best SNR and minimal artifact. In addition, the auto-PILS method is most efficient in scan time reduction. Interestingly, SMASH is not optimal for use with the highly localized coils with coil width on the same order as the voxel size
  • Keywords
    biomedical MRI; image reconstruction; medical image processing; 64-channel phased-array data; GRAPPA; PILS; SEA; SENSE; SMASH; SNR; SPACE-RIP; artifact power; auto-PILS; highly accelerated parallel imaging; image reconstruction; localized massive array coils; parallel MRI; scan efficiency; Acceleration; Coils; High definition video; Image reconstruction; Image sampling; Magnetic resonance imaging; Neoplasms; Phased arrays; Reconstruction algorithms; Torso;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Imaging: Nano to Macro, 2006. 3rd IEEE International Symposium on
  • Conference_Location
    Arlington, VA
  • Print_ISBN
    0-7803-9576-X
  • Type

    conf

  • DOI
    10.1109/ISBI.2006.1625021
  • Filename
    1625021