平滑的
成像体模
采样(信号处理)
奇异值分解
维数(图论)
电磁线圈
灵敏度(控制系统)
信噪比(成像)
体素
信号(编程语言)
噪音(视频)
核磁共振
数学
计算机科学
算法
人工智能
物理
光学
统计
工程类
电子工程
计算机视觉
滤波器(信号处理)
量子力学
纯数学
图像(数学)
程序设计语言
作者
Wanqi Hu,Huiting Liu,Dicheng Chen,Tianyu Qiu,Hongwei Sun,Chunyan Xiong,Jianzhong Lin,Di Guo,Hao Chen,Xiaobo Qu
出处
期刊:Molecules
[MDPI AG]
日期:2021-06-25
卷期号:26 (13): 3896-3896
被引量:6
标识
DOI:10.3390/molecules26133896
摘要
Magnetic resonance spectroscopy (MRS), as a noninvasive method for molecular structure determination and metabolite detection, has grown into a significant tool in clinical applications. However, the relatively low signal-to-noise ratio (SNR) limits its further development. Although the multichannel coil and repeated sampling are commonly used to alleviate this problem, there is still potential room for promotion. One possible improvement way is combining these two acquisition methods so that the complementary of them can be well utilized. In this paper, a novel coil-combination method, average smoothing singular value decomposition, is proposed to further improve the SNR by introducing repeatedly sampled signals into multichannel coil combination. Specifically, the sensitivity matrix of each sampling was pretreated by whitened singular value decomposition (WSVD), then the smoothing was performed along the repeated samplings’ dimension. By comparing with three existing popular methods, Brown, WSVD, and generalized least squares, the proposed method showed better performance in one phantom and 20 in vivo spectra.
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