SPATIOTEMPORAL DENOISING OF MR SPECTROSCOPIC IMAGING DATA BY LOW-RANK APPROXIMATIONS

被引：0
|
作者：
Nguyen, Hien M. [1 ]
Peng, Xi [1 ]
Do, Minh N. [1 ]
Liang, Zhi-Pei [1 ]
机构：
[1] Univ Illinois, Dept Elect & Comp Engn, Urbana, IL 61801 USA
来源：
2011 8TH IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: FROM NANO TO MACRO | 2011年
关键词：
MR spectroscopic imaging; denoising; low-rank approximation; partially-separable functions; Cadzow enhancement; RECONSTRUCTION; ENHANCEMENT; SLIM;
D O I：
暂无
中图分类号：
R318 [生物医学工程];
学科分类号：
0831 ;
摘要：
This paper addresses the denoising problem associated with magnetic resonance spectroscopic imaging (MRSI), where low 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 is due to linear predictability. Experimental results from practical data demonstrate that the proposed method provides an effective way to denoise MRSI data while preserving spatial-spectral features in a wide range of SNR values.
引用
收藏
页码：857 / 860
页数：4
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