RESULTS: We enhance the reconstruction quality of NUS symmetrical NMR spectroscopy based on the assumption that the asymmetry in intensity is mild. Regarding the sampling schedule, we employ the symmetrical sampling structure integrated with Poisson sampling schedule to enhance the efficiency of data acquisition. In term of the reconstruction algorithm, we propose the new method by incorporating hard and soft symmetrical constraints into our recently developed L1-norm-based Compressed Sensing (CS) method known as Sparse Complex-valued REconstruction Enabled by Newton method (SCREEN). Additionally, we propose a two-step reconstruction strategy that separately addresses diagonal and cross peaks. In this two-step strategy, cross peaks are effectively reconstructed by excluding the stronger diagonal peaks. Extensive experimental results validate the effectiveness of our proposed methodology.
CONCLUSIONS: This method enhances the overall quality of the reconstructed NUS symmetrical NMR spectra, especially in terms of cross peaks, thereby enriching the interpretation of spectral information. Furthermore, it boosts the robustness towards regularization parameters, facilitating a user-friendly experience.
结果:我们基于强度不对称性轻度的假设来增强NUS对称NMR光谱的重建质量。关于抽样时间表,我们采用对称采样结构与泊松采样计划集成,以提高数据采集的效率。就重建算法而言,我们通过将硬和软对称约束纳入我们最近开发的基于L1范数的压缩感知(CS)方法提出了新方法,该方法被称为稀疏复值重建牛顿法(SCREEN)。此外,我们提出了一个两步重建策略,分别解决对角和交叉峰。在这两步走的战略中,交叉峰通过排除较强的对角峰有效地重建。大量的实验结果验证了我们提出的方法的有效性。
结论:该方法提高了重建的NUS对称NMR光谱的整体质量,特别是在交叉峰方面,从而丰富了光谱信息的解释。此外,它提高了对正则化参数的鲁棒性,促进用户友好的体验。