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Publication Detail
Correct A Priori Information Modelling for Sparse MRI Reconstruction
  • Publication Type:
    Conference presentation
  • Authors:
    Ehrhardt M, Thielemans K, Pizarro L, Markiewicz P, Atkinson D, Ourselin S, Hutton B, Arridge S
  • Status:
    Accepted
  • Name of Conference:
    Sparsity Techniques in Medical Imaging (STMI2014)
  • Conference place:
    Boston, USA
  • Conference start date:
    14/09/2014
  • Conference finish date:
    18/09/2014
Abstract
Magnetic Resonance Imaging (MRI) is a non-ionizing, non-invasive, in-vivo imaging technique with a wide range of applications. Due to the sequential acquisition of the data the scan time can be quite long. To monitor dynamic processes or to enhance patient’s comfort the acquisition of some data can be replaced by a priori knowledge of the object known as sparse MRI. Although MRI images consists of complex numbers, the a priori information is often motivated by magnitude images but priors based on complex numbers are then implemented. We show what total variation of a complex image means and relate it to its analogue in colour image processing. Better modelling of the a priori knowledge is based on a different parametrization in terms of magnitude and phase and we analyse the resulting new data term. The numerical results show that with this modification images with a lot less artefacts can be reconstructed so that the acquisition time can be further reduced.
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