Arterial spin labeling perfusion MRI signal denoising using robust principal component analysis
Arterial spin labeling perfusion MRI signal denoising using robust principal component analysis
复制标题
使用稳健的主成分分析进行动脉自旋标记灌注 MRI 信号去噪
DOI：
10.1016/j.jneumeth.2017.11.017
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发表时间：
2018-02
影响因子：
3
通讯作者：
Wang Ze
中科院分区：
文献类型：
--
作者：
Zhu Hancan;Zhang Jian;Wang Ze
背景动脉自旋标记（ASL）灌注MRI提供了一种非侵入性的方法来量化局部脑血流量（CBF），并已越来越多地用于表征由于疾病或功能改变而引起的脑状态变化。然而，它在动态脑活动研究中的使用仍然受到ASL数据相对较低的信噪比（SNR）的阻碍。新方法本研究的目的是验证一种新的时间去噪策略ASL MRI。使用鲁棒主成分分析（rPCA）将ASL CBF图像系列分解为低秩分量和稀疏分量。前者捕获缓慢波动的灌注模式，而后者表示空间不相干的尖峰变化，并作为噪声被丢弃。虽然仍然缺乏一种方法来确定用于控制分解的低秩和稀疏性之间的平衡的参数，我们设计了一种方法来解决这个问题的基础上独特的数据结构的ASL MRI。方法采用基于ASL脑血流的功能连通性（FC）分析和感觉运动功能ASL MRI研究，与现有方法进行比较，并与基于成分的噪声校正方法（CompCor）进行比较。结论我们提出了一种新的时间ASL CBF图像去噪方法，该方法可用于基于CBF时间序列的FC分析和任务激活检测。
BackgroundArterial spin labeling (ASL) perfusion MRI provides a non-invasive way to quantify regional cerebral blood flow (CBF) and has been increasingly used to characterize brain state changes due to disease or functional alterations. Its use in dynamic brain activity study, however, is still hampered by the relatively low signal-to-noise-ratio (SNR) of ASL data.New methodThe aim of this study was to validate a new temporal denoising strategy for ASL MRI. Robust principal component analysis (rPCA) was used to decompose the ASL CBF image series into a low-rank component and a sparse component. The former captures the slowly fluctuating perfusion patterns while the latter represents spatially incoherent spiky variations and was discarded as noise. While there still lacks a way to determine the parameter for controlling the balance between the low-rankness and sparsity of the decomposition, we designed a method to solve this problem based on the unique data structures of ASL MRI. Method evaluations were performed with ASL CBF-based functional connectivity (FC) analysis and a sensorimotor functional ASL MRI study.Comparison with existing method(s)The proposed method was compared with the component based noise correction method (CompCor).ResultsThe proposed method markedly increased temporal signal-to-noise-ratio (TSNR) and sensitivity of ASL CBF images for FC analysis and task activation detection.ConclusionsWe proposed a new temporal ASL CBF image denoising method, and showed its benefit for the CBF time series-based FC analysis and task activation detection.
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影响因子：
3.3
作者：
Chiew M;Smith SM;Koopmans PJ;Graedel NN;Blumensath T;Miller KL
通讯作者：
Miller KL
影响因子：
4.8
作者：
Wang, Ze
通讯作者：
Wang, Ze
DOI：
10.1007/978-3-642-58716-0_6
发表时间：
2000
期刊：
--
影响因子：
--
作者：
E. Wong
通讯作者：
E. Wong
影响因子：
4.4
作者：
Li, Zhengjun;Kadivar, Aniseh;Pluta, John;Dunlop, John;Wang, Ze
通讯作者：
Wang, Ze
DOI：
10.1007/s10334-010-0209-8
发表时间：
2010-06-01
影响因子：
2.3
作者：
Bibic, Adnan;Knutsson, Linda;Wirestam, Ronnie
通讯作者：
Wirestam, Ronnie