Wavelet-regularized reconstruction for rapid MRI

Author

Guerquin-Kern, M. ; Van De Ville, D. ; Vonesch, C. ; Baritaux, J.-C. ; Pruessmann, K.P. ; Unser, M.

Author_Institution

Biomed. Imaging Group, Ecole Polytech. Fed. de Lausanne, Lausanne, Switzerland

fYear

2009

fDate

June 28 2009-July 1 2009

Firstpage

193

Lastpage

196

Abstract

We propose a reconstruction scheme adapted to MRI that takes advantage of a sparsity constraint in the wavelet domain. We show that artifacts are significantly reduced compared to conventional reconstruction methods. Our approach is also competitive with total variation regularization both in terms of MSE and computation time. We show that lscr¹ regularization allows partial recovery of the missing k-space regions. We also present a multi-level version that significantly reduces the computational cost.

Keywords

biomedical MRI; image reconstruction; medical image processing; wavelet transforms; MRI; MSE; reconstruction; total variation regularization; wavelet domain; Biomedical imaging; Biomedical measurements; Compressed sensing; Fourier transforms; Image reconstruction; Image sampling; Magnetic field measurement; Magnetic resonance imaging; Reconstruction algorithms; Wavelet domain; MRI; compressed sensing; multi-level strategy; non-linear reconstruction; sparsity; thresholded Landweber; wavelets;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Imaging: From Nano to Macro, 2009. ISBI '09. IEEE International Symposium on

Conference_Location

Boston, MA

ISSN

1945-7928

Print_ISBN

978-1-4244-3931-7

Electronic_ISBN

1945-7928

Type

conf

DOI

10.1109/ISBI.2009.5193016

Filename

5193016