6533b82ffe1ef96bd1295ace
RESEARCH PRODUCT
Denoising of MR spectroscopy signals using total variation and iterative Gauss-Seidel gradient updates
Roger P. WoodsStephanie NjauKatherine L. NarrShantanu H. JoshiAntonio Marquinasubject
Free induction decayReduction (complexity)Mathematical optimizationSignal-to-noise ratioNoise reductionGauss–Seidel methodRingingTotal variation denoisingSpectroscopyAlgorithmMathematicsdescription
We present a fast variational approach for denoising signals from magnetic resonance spectroscopy (MRS). Differently from the TV approaches applied to denoising of images, this is the first time to our knowledge that it has been used for the processing of free induction decay signals from single-voxel spectroscopy (SVS) acquisitions. Another novelty in this study is the direct use of the Euler Lagrange formulation coupled with Gauss Seidel gradient updates to improve the speed of iteration and reduce ringing. Results from brain MRS signals show improvement in signal to noise ratio as well as reduction in estimation error in the quantification of metabolites.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2015-04-01 | 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI) |