This work proposes a method to accelerate the acquisition of high-quality edited magnetic resonance spectroscopy (MRS) scans using machine learning models taking the sample covariance matrix as input. The method is invariant to the number of transients and robust to noisy input data for both synthetic as well as in-vivo scenarios.

翻译：本工作提出了一种利用机器学习模型加速高质量编辑磁共振波谱（MRS）扫描采集的方法，该方法将样本协方差矩阵作为输入。该方案对瞬态数量具有不变性，且在合成数据及体内场景中均对噪声输入数据具有鲁棒性。