| Wavelet-Regularized MRI Reconstruction |
Investigators: Matthieu Guerquin-Kern, Ulugbek Kamilov |
|
Summary: We develop fast algorithms with wavelet regularization for general acquisition schemes in Magnetic Resonance Imaging. We also develop tools for the validation of MRI reconstruction methods.
|
|
Classical MRI uses Cartesian sampling in k-space which facilitates the reconstruction process (simple inverse Fourier transform). Currently, the research focus is on more-general acquisition schemes (e.g., non-Cartesian, or with missing data) that offer more flexibility, but require more-complicated reconstruction procedures. The state-of-the-art algorithms are linear, but there is evidence that the quality of reconstruction can be improved by using nonlinear iterative techniques. |
|
To have a better-conditioned reconstruction problem, we propose to favor solutions that have a sparse representation in the wavelet domain (which is the case for natural-looking images). Our mathematical efforts will focus on the design of an algorithm with fast convergence that exploits the specificity of the problem settings. As a first step, we design an algorithm adapted to the single-coil case that can handle general non-Cartesian k-space sampling. Next, we extend it to the multiple-coil problem. We validate the reconstruction process on to both simulated and real data. We obtain equal or superior results in quality and speed with respect to the current state-of-the-art techniques. |
|
Collaborations: Michael Unser, K.P. Prüssmann (ETHZ) |
|
|
|
|
[2] | M. Guerquin-Kern, J.-C. Baritaux, M. Unser, "Efficient Image Reconstruction Under Sparsity Constraints with Application to MRI and Bioluminescence Tomography," Proceedings of the Thirty-Sixth IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP'11), Prague, Czech Republic, May 22-27, 2011, pp. 5760-5763.
|
[3] | M. Guerquin-Kern, F.I. Karahanoğlu, D. Van De Ville, K.P. Pruessmann, M. Unser, "Analytical Form of Shepp-Logan Phantom for Parallel MRI," Proceedings of the Seventh IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI'10), Rotterdam, The Netherlands, April 14-17, 2010, pp. 261-264.
|
|
|
|
