Jiang Ziling, Wang Xianli, Chu Kaiqin, Smith Zachary J
University of Science and Technology of China, Department of Precision Machinery & Precision Instrumentation, Hefei, Anhui, China 230027.
University of Science and Technology of China, Suzhou Institute for Advanced Research, Suzhou, Jiangsu, China 215123.
Analyst. 2023 Sep 25;148(19):4710-4720. doi: 10.1039/d3an00997a.
Raman hyperspectral imaging is an effective method for label-free imaging with chemical specificity, yet the weak signals and correspondingly long integration times have hindered its wide adoption as a routine analytical method. Recently, low resolution Raman imaging has been proposed to improve the spectral signal-to-noise ratio, which significantly improves the speed of Raman imaging. In this paper, low resolution Raman spectroscopy is combined with "context-aware" matrix completion, where regions of the sample that are not of interest are skipped, and the regions that are measured are under-sampled, then reconstructed with a low-rank constraint. Both simulations and experiment show that low-resolution Raman boosts the speed and image quality of the computationally-reconstructed Raman images, allowing deeper sub-sampling, reduced exposure time, and an overall >10-fold improvement in imaging speed, without sacrificing chemical specificity or spatial image quality. As the method utilizes traditional point-scan imaging, it retains full confocality and is "backwards-compatible" with pre-existing traditional Raman instruments, broadening the potential scope of Raman imaging applications.
拉曼高光谱成像技术是一种有效的无标记成像方法，具有化学特异性，但信号较弱且积分时间相应较长，这阻碍了它作为常规分析方法的广泛应用。最近，有人提出采用低分辨率拉曼成像来提高光谱信噪比，这显著提高了拉曼成像的速度。在本文中，低分辨率拉曼光谱与“上下文感知”矩阵补全相结合，即跳过样本中不感兴趣的区域，对测量区域进行欠采样，然后通过低秩约束进行重建。模拟和实验均表明，低分辨率拉曼技术提高了计算重建拉曼图像的速度和图像质量，允许进行更深层次的欠采样、缩短曝光时间，并且在不牺牲化学特异性或空间图像质量的情况下，整体成像速度提高了10倍以上。由于该方法采用传统的点扫描成像，它保留了完全共焦性，并且与现有的传统拉曼仪器“向后兼容”，拓宽了拉曼成像应用的潜在范围。
