Denoising MR Spectroscopic Imaging Data with Low-Rank Approximations

	Denoising MR Spectroscopic Imaging Data with Low-Rank Approximations
	Hien Nguyen; Xi Peng; Minh Do; Zhi-Pei Liang
刊名	IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
	2013
英文摘要	This paper addresses the denoising problem associated with magnetic resonance spectroscopic imaging (MRSI), where signal-to-noise ratio (SNR) has been a critical problem. A new scheme is proposed, which exploits two low-rank structures that exist in MRSI data, one due to partial separability and the other due to linear predictability. Denoising is performed by arranging the measured data in appropriate matrix forms (i.e., Casorati and Hankel) and applying low-rank approximations by singular value decomposition (SVD). The proposed method has been validated using simulated and experimental data, producing encouraging results. Specifically, the method can effectively denoise MRSI data in a wide range of SNR values while preserving spatial-spectral features. The method could prove useful for denoising-MRSI data and other spatial-spectral and spatial-temporal imaging data as well.
收录类别	SCI
原文出处	http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6327614
语种	英语
内容类型	期刊论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/4776]
专题	深圳先进技术研究院_医工所
作者单位	IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
推荐引用方式 GB/T 7714	Hien Nguyen,Xi Peng,Minh Do,et al. Denoising MR Spectroscopic Imaging Data with Low-Rank Approximations[J]. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING,2013.
APA	Hien Nguyen,Xi Peng,Minh Do,&Zhi-Pei Liang.(2013).Denoising MR Spectroscopic Imaging Data with Low-Rank Approximations.IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING.
MLA	Hien Nguyen,et al."Denoising MR Spectroscopic Imaging Data with Low-Rank Approximations".IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING (2013).