Sparsity & Compressed Sensing
Aurelien Bustin1
1IHU Liryc – Electrophysiology and heart modeling institute, Bordeaux, France

Synopsis

Keywords: Image acquisition: Fast imaging

In this presentation, we will delve into the fascinating world of compressed sensing, which allows for measuring less data during imaging procedures. We will explore the three fundamental ingredients of compressed sensing: sparsity, random acquisition, and non-linear reconstruction. We will delve into each component, exploring their implementation and showcasing their remarkable potential in a range of clinical applications.

Synopsis

In this presentation, we will delve into the fascinating world of compressed sensing, which allows for measuring less data during imaging procedures. We will explore the three fundamental ingredients of compressed sensing: sparsity, random acquisition, and non-linear reconstruction. We will delve into each component, exploring their implementation and showcasing their remarkable clinical potential.

Acknowledgements

No acknowledgement found.

References

No reference found.

Figures


Proc. Intl. Soc. Mag. Reson. Med. 31 (2023)