Inversion of incomplete spectral data using support information with an application to magnetic resonance imaging

Inversion of incomplete spectral data using support information with an application to magnetic resonance imaging

de Leeuw den Bouter, M.L. (TU Delft Numerical Analysis)
van den Berg, P.M. (TU Delft ImPhys/Medical Imaging)
Remis, R.F. (TU Delft Signal Processing Systems)

2021

In this paper we discuss an imaging method when the object has known support and its spatial Fourier transform is only known on a certain k-space undersampled pattern. The simple conjugate gradient least squares algorithm applied to the corresponding truncated Fourier transform equation produces reconstructions that are basically of a similar quality as reconstructions obtained by solving a standard compressed sensing problem in which support information is not taken into account. Connections with previous one-dimensional approaches are highlighted and the performance of the method for two-and three-dimensional simulated and measured incomplete spectral data sets is illustrated. Possible extensions of the method are also briefly discussed.

Compressed sensing
Image reconstruction
Incomplete spectral data
Low-field MRI
Magnetic resonance imaging (MRI)
Support information
OA-Fund TU Delft

http://resolver.tudelft.nl/uuid:24ddf0a9-3edd-45ac-be20-5fe918b97e20

https://doi.org/10.1088/2399-6528/abfd45

Journal of Physics Communications, 5 (5), 1-13

Institutional Repository

journal article

© 2021 M.L. de Leeuw den Bouter, P.M. van den Berg, R.F. Remis