|Title:||An adaptive directional haar framelet-based reconstruction algorithm for parallel magnetic resonance imaging||Authors:||Li, Y.-R.
WEN-YIH ISAAC TSENG
|Keywords:||Haar wavelet system | Parallel MRI | Proximity operator | Tight frame | Total variation||Issue Date:||2016||Journal Volume:||9||Journal Issue:||2||Source:||SIAM Journal on Imaging Sciences||Abstract:||
© 2016 Society for Industrial and Applied Mathematics. Parallel magnetic resonance imaging (pMRI) is a technique to accelerate the magnetic resonance imaging process. The problem of reconstructing an image from the collected pMRI data is ill-posed. Regularization is needed to make the problem well-posed. In this paper, we first construct a twodimensional tight framelet system whose filters have the same support as the orthogonal Haar filters and are able to detect edges of an image in the horizontal, vertical, and ±45° directions. This system is referred to as directional Haar framelet (DHF). We then propose a pMRI reconstruction model whose regularization term is formed by the DHF. This model is solved by a fast proximal algorithm with low computational complexity. The regularization parameters are updated adaptively and determined automatically during the iteration of the algorithm. Numerical experiments for in-silico and in-vivo data sets are provided to demonstrate the superiority of the DHF-based model and the efficiency of our proposed algorithm for pMRI reconstruction.
|Appears in Collections:||醫療器材與醫學影像研究所|
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