Lowering the thermal noise barrier in functional brain mapping with magnetic resonance imaging.

Lowering the thermal noise barrier in functional brain mapping with magnetic resonance imaging.
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DOI:
10.1038/s41467-021-25431-8
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发表时间:
2021-08-30
影响因子:
16.6
通讯作者:
Uğurbil K
Uğurbil K
中科院分区:
综合性期刊1区
文献类型:
--
作者:
Vizioli L;Moeller S;Dowdle L;Akçakaya M;De Martino F;Yacoub E;Uğurbil K

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功能磁共振成像(FMRI)已成为研究人脑不可或缺的工具。然而,fMRI测量固有的低信噪比(SNR)是扩展其时空尺度的主要障碍,也是其实用性和最终影响的主要障碍。在这里,我们介绍了一种去噪技术,它选择性地抑制热噪声对fMRI实验的贡献。使用7特斯拉高分辨率人脑数据,我们展示了功能图关键指标(时间信噪比、刺激诱导信号变化的检测和重复性以及功能图的准确性)的改进,同时保持刺激诱导信号变化的幅度、空间精度和功能点扩散函数不变。我们证明,该方法能够获得超高分辨率(0.5Tesla mm各向同性)功能图,但对于多种功能磁共振成像应用也同样有益,包括在不同刺激/任务范例和获取策略下在不同皮质区域获得的超毫米分辨率3-和7- 数据。在选择磁共振成像方案时,信噪比是一个关键的考虑因素。热噪声是一个主要问题,尤其是在高分辨率功能图像中。本文介绍了一种在不损失空间精度的情况下抑制功能图像中热噪声的方法,从而提高了信噪比。
Functional magnetic resonance imaging (fMRI) has become an indispensable tool for investigating the human brain. However, the inherently poor signal-to-noise-ratio (SNR) of the fMRI measurement represents a major barrier to expanding its spatiotemporal scale as well as its utility and ultimate impact. Here we introduce a denoising technique that selectively suppresses the thermal noise contribution to the fMRI experiment. Using 7-Tesla, high-resolution human brain data, we demonstrate improvements in key metrics of functional mapping (temporal-SNR, the detection and reproducibility of stimulus-induced signal changes, and accuracy of functional maps) while leaving the amplitude of the stimulus-induced signal changes, spatial precision, and functional point-spread-function unaltered. We demonstrate that the method enables the acquisition of ultrahigh resolution (0.5 mm isotropic) functional maps but is also equally beneficial for a large variety of fMRI applications, including supra-millimeter resolution 3- and 7-Tesla data obtained over different cortical regions with different stimulation/task paradigms and acquisition strategies. The signal-to-noise ratio is a key consideration when selecting a magnetic resonance imaging protocol. Thermal noise is major issue, especially in high resolution functional images. Here the authors introduce a method to suppress thermal noise in functional images without losses in spatial precision, increasing the signal-to-noise ratio.
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