Stationary wavelet transform for under-sampled MRI reconstruction.

@article{Kayvanrad2014StationaryWT,
  title={Stationary wavelet transform for under-sampled MRI reconstruction.},
  author={Mohammad H. Kayvanrad and A. Jonathan McLeod and John Stuart Haberl Baxter and Charles A. McKenzie and Terry M. Peters},
  journal={Magnetic resonance imaging},
  year={2014},
  volume={32 10},
  pages={
          1353-64
        }
}
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25 Citations
Background Citations
10
Methods Citations
7

25 Citations

Fast Compressed Sensing MRI Based on Complex Double-Density Dual-Tree Discrete Wavelet Transform
TLDR
A CS-based reconstruction scheme, which combines complex double-density dual-tree discrete wavelet transform (CDDDT-DWT) with fast iterative shrinkage/soft thresholding algorithm (FISTA) to efficiently reduce visual artifacts in undersampled MRI reconstruction.
CORE‐PI: Non‐iterative convolution‐based reconstruction for parallel MRI in the wavelet domain
TLDR
COnvolution-based REconstruction for Parallel MRI advantageously offers a flexible 1D undersampling of a Cartesian k-space, a parameter-free non-iterative implementation, reconstruction performance comparable or better than that of GRAPPA and l1-SPIRiT, and robust fast computations.
Joint Inverse Problems for Signal Reconstruction via Dictionary Splitting
TLDR
This work proposes a dictionary splitting approach for sparse recovery from incomplete data, which leverages the ideas of cycle spinning in combination with Bregman splitting, and significantly reduces its computational cost and redundancy factor.
Projected Iterative Soft-Thresholding Algorithm for Tight Frames in Compressed Sensing Magnetic Resonance Imaging
TLDR
It is proved that pISTA and pFISTA converge to a minimizer of a convex function with a balanced tight frame sparsity formulation, and leads to faster convergence speeds than the state-of-art counterpart does, while achieving comparable reconstruction errors.
A guaranteed convergence analysis for the projected fast iterative soft-thresholding algorithm in parallel MRI
CS-MRI reconstruction via group-based eigenvalue decomposition and estimation
CORE-Deblur: Parallel MRI Reconstruction by Deblurring using compressed sensing.
Exponential Wavelet Iterative Shrinkage Thresholding Algorithm for compressed sensing magnetic resonance imaging
Variable Splitting and Cycle Spinning for Sparse Signal Recovery
We propose a variable splitting approach for sparse recovery from incomplete Fourier data, which significantly improves conventional wavelet-based compressed sensing/reconstruction, offers the…
Sparse MRI reconstruction using multi-contrast image guided graph representation.
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References

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