Title
Denoising Of Mr Spectroscopy Signals Using Total Variation And Iterative Gauss-Seidel Gradient Updates
Abstract
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
Venue
Keywords
2015
2015 IEEE 12TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI)
magnetic resonance spectroscopy, denoising, total variation, Gauss Seidel
Field
DocType
ISSN
Noise reduction,Computer science,Total variation denoising,Artificial intelligence,Free induction decay,Mathematical optimization,Pattern recognition,Ringing,Signal-to-noise ratio,Algorithm,In vivo magnetic resonance spectroscopy,Spectroscopy,Gauss–Seidel method
Conference
1945-7928
Citations 
PageRank 
References 
0
0.34
7
Authors
5
Name
Order
Citations
PageRank
Shantanu H. Joshi184550.12
Antonio Marquina243145.30
Stephanie Njau300.34
Katherine L. Narr439724.00
Roger P. Woods5602115.30