How to Efficiently Travel Through k-Space
Shahrzad Moinian1
1Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia

Synopsis

Keywords: Physics & Engineering: Physics, Image acquisition: Reconstruction

MRI scanners measure and store MRI signals in the form of a 2D/3D data matrix, called k-space. K-space contains spatial frequency information which is acquired through phase and frequency encoding. The k-space spatial frequency information can be used to reconstruct MR images using inverse Fourier transform. This lecture will introduce the basic concepts of k-space in MR image acquisition and reconstruction. It will give an overview of different k-space trajectories and the effect of MRI acquisition parameters on k-space data. Finally, we will learn about k-space under-sampling and how it can be used in fast MR imaging.

Target Audience

Beginner to intermediate scientists or clinician-scientists, including trainees (students and fellows). While no prior knowledge is required, a basic understanding of the concepts behind nuclear spin would be beneficial.

Learning Objectives

  • Understand the basic concepts of k-space [1] and how to reconstruct MR images from k-space data using inverse Fourier Transform (see Figure 1)
  • Understand how MR image acquisition parameters affect k-space and thereby the reconstructed images
  • Learn about most common k-space trajectories [2]
  • Learn about k-space under-sampling and how it can be used in fast MR imaging
  • Learn about two main parallel imaging techniques (GRAPPA [3] & SENSE [4]) and how k-space data is acquired and processed in these techniques

Acknowledgements

I have no financial interests or relationships to disclose with regard to the subject matter of this presentation.

References

[1] Mezrich R. A perspective on K-space. Radiology. 1995 May;195(2):297-315.

[2] Hennig J. K-space sampling strategies. European radiology. 1999 Jul 1;9(6):1020.

[3] Griswold MA, Jakob PM, Heidemann RM, Nittka M, Jellus V, Wang J, Kiefer B, Haase A. Generalized autocalibrating partially parallel acquisitions (GRAPPA). Magnetic Resonance in Medicine: An Official Journal of the International Society for Magnetic Resonance in Medicine. 2002 Jun;47(6):1202-10.

[4] Pruessmann KP, Weiger M, Scheidegger MB, Boesiger P. SENSE: sensitivity encoding for fast MRI. Magnetic Resonance in Medicine: An Official Journal of the International Society for Magnetic Resonance in Medicine. 1999 Nov;42(5):952-62.

Figures

K-space represents spatial frequency information, acquired by MRI scanners. MR images can be reconstructed from k-space data using inverse Fourier Transform. K-space properties affect the reconstructed images in terms of image resolution, field-of-view (FOV), signal-to-noise ratio (SNR), aliasing artifacts, etc.

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