Title :
Denoising of MR spectroscopic imaging data with spatial-spectral regularization
Author :
Nguyen, Hien M. ; Haldar, Justin P. ; Do, Minh N. ; Liang, Zhi-Pei
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
Abstract :
Low signal-to-noise ratio has been a significant limitation for clinical applications of magnetic resonance spectroscopic imaging (MRSI). This paper investigates a new scheme for denoising MRSI data, incorporating both an anatomically-adapted spatial-smoothness constraint and an autoregressive spectral constraint within the penalized maximum-likelihood framework. Both theoretical analysis and simulation results are provided to characterize the denoising performance of this approach.
Keywords :
autoregressive processes; biomedical MRI; image denoising; magnetic resonance spectroscopy; maximum likelihood estimation; MR spectroscopy; autoregressive spectral constraint; image denoising; magnetic resonance spectroscopic imaging; penalized maximum-likelihood framework; signal-to-noise ratio; spatial-smoothness constraint; spatial-spectral regularization; Biological system modeling; Magnetic resonance; Magnetic resonance imaging; Noise measurement; Noise reduction; Nonlinear filters; Signal to noise ratio; Smoothing methods; Spatial resolution; Spectroscopy;
Conference_Titel :
Biomedical Imaging: From Nano to Macro, 2010 IEEE International Symposium on
Conference_Location :
Rotterdam
Print_ISBN :
978-1-4244-4125-9
Electronic_ISBN :
1945-7928
DOI :
10.1109/ISBI.2010.5490073
