This paper presents a new accelerated fMRI reconstruction method, namely, OptShrink LR + S method that reconstructs undersampled fMRI data using a linear combination of low-rank and sparse components. The low-rank component has been estimated using non-convex optimal singular value shrinkage algorithm, while the sparse component has been estimated using convex l 1 minimization. The performance of the proposed method is compared with the existing state-of-the-art algorithms on real fMRI dataset. The proposed OptShrink LR + S method yields good qualitative and quantitative results.

中文翻译：

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Optshrink LR + S：使用非凸最佳奇异值收缩来加速fMRI重建。

本文提出了一种新的加速fMRI重建方法，即OptShrink LR + S方法，该方法使用低秩和稀疏分量的线性组合重建欠采样的fMRI数据。使用非凸最优奇异值收缩算法来估计低秩分量，而使用凸l 1最小化来估计稀疏分量。将该方法的性能与真实fMRI数据集上现有的最新算法进行了比较。拟议的OptShrink LR + S方法产生了良好的定性和定量结果。