IS = { zkontrolovano 15 Jan 2008 },
  UPDATE  = { 2007-11-28 },
  author =      {Petr, Jan},
  title =       {Parallel Magnetic Resonance Imaging Reconstruction},
  year =        {2007},
  pages =       {129},
  school =      {Czech Technical University in Prague},
  address =     {Prague, Czech Republic},
  day =         {24},
  month =       {October},
  isbn =        {1213-2365},
  figures =     {68},
  appendices =  {1},
  supervisor =  {Kybic, Jan},
  annote = {The acquisition speed of magnetic resonance imaging (MRI)
    is an important issue. Increasing the acquisition speed shortens
    the total patient examination time, it reduces motion artifacts
    and increases the frame rate of dynamic MRI. Parallel MRI is a way
    to use multiple receiver coils with distinct spatial sensitivities
    to increase the MRI acquisition speed. The acquisition is speeded
    up by undersampling the k-space in the phase-encoding
    direction. The resulting data loss and consequent aliasing is
    compensated for by the use of additional information obtained from
    several receiver coils.  In this thesis, we summarize the
    state-of-the-art in parallel MRI area. We also provide the
    theoretical background of MRI because full understanding of the
    principles behind parallel MRI is needed to understand its further
    extension. The main contribution of this thesis is a novel
    parallel MRI method. Our method takes advantage of the smoothness
    of the reconstruction transformation in space. B-spline functions
    are used to approximate the reconstruction transformation. This
    reduces the number of the reconstruction parameters and makes the
    method more robust especially in areas with low signal-to-noise
    ratio. The B-spline coefficients are estimated by minimizing the
    total expected reconstruction error.  We compare our new method
    theoretically and experimentally with two commercially available
    methods - SENSE and GRAPPA. The experiments were performed on
    simulated, phantom and in-vivo images. We show that our method
    outperforms the SENSE and GRAPPA reconstruction methods on a
    considerable number of input images and reaches the same quality
    on the rest.},
  keywords =    {restoration, parallel MRI, magnetic resonance, 
                 B-spline, SENSE, GRAPPA},
  project =     {1ET101050403, CTU0505713, CTU0614913, 
                 GACR 102/03/0440, MSM6840770012},
  psurl       = {[PDF, 5MB] },