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Publication Detail
Direct parametric reconstruction from undersampled (k, t)-space data in dynamic contrast enhancement MRI
  • Publication Type:
    Journal article
  • Authors:
    Dikaios N, Atkinson D
  • Publication date:
    27/11/2013
  • Status:
    Accepted
  • Country:
    Seoul, Korea
  • Keywords:
    Direct reconstruction, MRI, DCE
Abstract
The aim in this paper is to estimate kinetic parameters from undersampled (k, t)-space dynamic contrast enhancement (DCE) MRI. DCE requires high temporal resolution to capture enhancement processes that occur rapidly. Undersampling can accelerate the acquisition but will result in image degradation. Typically the DCE images are reconstructed separately, and kinetic parameters are estimated by fitting a pharmacokinetic model to the time-enhancement response and can be characterized as an “indirect” approach. The direct parametric reconstruction from (k, t)-space is implemented as a Metropolis–Hastings Bayesian inference algorithm. The proposed algorithm promotes sparsity through the kinetic parameters, using a Laplacian density function. The estimated kinetic parameters from undersampled data with the proposed algorithm improves correlation with the kinetic parameters estimated by fully sampled data, by 7% and 11% for 4-fold and 8-fold undersampling respectively, compared to the “indirect” approach.
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