• DocumentCode
    2377516
  • Title

    Iterative image reconstruction model including susceptibility gradients combined with Z-shimming gradients in fMRI

  • Author

    Zhuo, Yue ; Sutton, Bradley P.

  • Author_Institution
    Bioeng. Dept., Univ. of Illinois at Urbana-Champaign, Champaign, IL, USA
  • fYear
    2009
  • fDate
    3-6 Sept. 2009
  • Firstpage
    5721
  • Lastpage
    5724
  • Abstract
    Magnetic susceptibility artifacts, including both image distortions and signal losses, exist near air/tissue interfaces in the ventral brain in standard blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI). Although several acquisition-based approaches exist to address the signal losses, they require increased acquisition time or patient customization. In this work, we propose a statistical estimation model that includes the effects of magnetic field gradients (both within-plane and through-plane gradients) and uses an iterative reconstruction algorithm to reconstruct images corrected for both magnetic field distortion and signal losses. Besides, we combine our reconstruction approach with a recently proposed MRI sequence with Z-shimming gradient between the spiral-in and spiral-out acquisition to enhance the compensation for signal losses. Therefore, we extend our forward MR signal model to include the physics of susceptibility-induced magnetic field (SF), susceptibility-induced magnetic field gradients (SFG), and the application of the data acquisition technique with Z-shimming Gradients (ZShG). The results show that not only signal distortions but also significant signal losses can be compensated by considering both the modeling of field-inhomogeneity effects along with the acquisition using Z-shimming.
  • Keywords
    biomedical MRI; blood; image reconstruction; iterative methods; magnetic susceptibility; medical image processing; oxygen; MRI sequence; Z-shimming gradient; blood oxygenation level dependence; data acquisition; fMRI; functional magnetic resonance imaging; image distortion; image reconstruction; iterative reconstruction algorithm; magnetic susceptibility; signal loss; statistical estimation model; susceptibility gradient; Algorithms; Brain; Evoked Potentials; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Magnetic Resonance Imaging; Models, Neurological; Phantoms, Imaging; Reproducibility of Results; Sensitivity and Specificity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE
  • Conference_Location
    Minneapolis, MN
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-3296-7
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/IEMBS.2009.5332669
  • Filename
    5332669