The goals of fMRI acquisition include high spatial and temporal resolutions with a high signal to noise ratio (SNR). Oscillating Steady-State Imaging (OSSI) is a new fMRI acquisition method that provides large oscillating signals with the potential for high SNR, but does so at the expense of spatial and temporal resolutions. The unique oscillation pattern of OSSI images makes it well suited for high-dimensional modeling. We propose a patch-tensor low-rank model to exploit the local spatial-temporal low-rankness of OSSI images. We also develop a practical sparse sampling scheme with improved sampling incoherence for OSSI. With an alternating direction method of multipliers (ADMM) based algorithm, we improve OSSI spatial and temporal resolutions with a factor of 12 acquisition acceleration and 1.3 mm isotropic spatial resolution in prospectively undersampled experiments. The proposed model yields high temporal SNR with more activation than other low-rank methods. Compared to the standard grad- ient echo (GRE) imaging with the same spatial-temporal resolution, 3D OSSI tensor model reconstruction demonstrates 2 times higher temporal SNR with 2 times more functional activation.

中文翻译：

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使用贴片张量低阶重建的高分辨率振荡稳态 fMRI。

fMRI 采集的目标包括高空间和时间分辨率以及高信噪比 (SNR)。振荡稳态成像 (OSSI) 是一种新的 fMRI 采集方法，可提供具有高信噪比潜力的大振荡信号，但这样做会牺牲空间和时间分辨率。OSSI 图像独特的振荡模式使其非常适合高维建模。我们提出了一种补丁张量低秩模型来利用 OSSI 图像的局部时空低秩性。我们还开发了一种实用的稀疏采样方案，改进了 OSSI 的采样不相干性。通过基于乘法器交替方向法 (ADMM) 的算法，我们在前瞻性欠采样实验中将 OSSI 空间和时间分辨率提高了 12 倍采集加速度和 1.3 毫米各向同性空间分辨率。所提出的模型比其他低秩方法产生更高的时间信噪比和更多的激活。与具有相同时空分辨率的标准梯度回波（GRE）成像相比，3D OSSI 张量模型重建显示出 2 倍高的时间 SNR 和 2 倍的功能激活。