Synopsis

Keywords: Image acquisition: Fast imaging

This tutorial will focus on discussing various dynamic imaging models for accelerated imaging. The models will be discussed in a unified perspective. Linear models such as view-sharing, UNFOLD, k-t BLAST,partial separability model (low-rank model) will first be discussed. Non-linear models such as compressed sensing, joint low rank and sparsity based, blind compressed sensing will then be reviewed. Imaging models without the need of explicit deformation estimation to perform motion resolved reconstruction such as extra-dimensional based models , manifold learning models will also be reviewed. Several application examples in free breathing cardiac, real time speech, free breathing liver DCE-MRI will be highlighted.

This tutorial will focus on discussing various dynamic imaging models for accelerated imaging. The models will be discussed in a unified perspective. Linear models such as view-sharing, UNFOLD, k-t BLAST dynamic imaging with learned temporal basis functions such as partial separability model (low-rank model) will first be discussed. Non-linear models such as compressed sensing, joint low rank and sparsity based, blind compressed sensing will then be reviewed. Imaging models without the need of explicit deformation estimation to perform motion resolved reconstruction such as extra-dimensional based models (eg. XDGRASP, MR multitasking), manifold learning models will also be reviewed. Several application examples in free breathing cardiac, real time speech, free breathing liver DCE-MRI will be highlighted.

Acknowledgements

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References

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