Troein Carl, Siregar Syahril, Beeck Michiel Op De, Peterson Carsten, Tunlid Anders, Persson Per
Department of Astronomy and Theoretical Physics, Lund University, 223 62 Lund, Sweden.
Department of Biology, Lund University, 223 62 Lund, Sweden.
Methods Protoc. 2020 May 1;3(2):34. doi: 10.3390/mps3020034.
Modern vibrational spectroscopy techniques enable the rapid collection of thousands of spectra in a single hyperspectral image, allowing researchers to study spatially heterogeneous samples at micrometer resolution. A number of algorithms have been developed to correct for effects such as atmospheric absorption, light scattering by cellular structures and varying baseline levels. After preprocessing, spectra are commonly decomposed and clustered to reveal informative patterns and subtle spectral changes. Several of these steps are slow, labor-intensive and require programming skills to make use of published algorithms and code. We here present a free and platform-independent graphical toolbox that allows rapid preprocessing of large sets of spectroscopic images, including atmospheric correction and a new algorithm for resonant Mie scattering with improved speed. The software also includes modules for decomposition into constituent spectra using the popular Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) algorithm, augmented by region-of-interest selection, as well as clustering and cluster annotation.
现代振动光谱技术能够在单个高光谱图像中快速采集数千个光谱，使研究人员能够以微米分辨率研究空间异质样本。已经开发了许多算法来校正诸如大气吸收、细胞结构的光散射和变化的基线水平等影响。预处理后，光谱通常会被分解和聚类，以揭示信息模式和细微的光谱变化。这些步骤中的几个步骤速度慢、劳动强度大，并且需要编程技能才能使用已发表的算法和代码。我们在此展示一个免费且独立于平台的图形工具箱，它允许对大量光谱图像进行快速预处理，包括大气校正和一种具有更高速度的用于共振米氏散射的新算法。该软件还包括使用流行的多元曲线分辨率交替最小二乘法（MCR-ALS）算法将光谱分解为组成光谱的模块，并通过感兴趣区域选择进行增强，以及聚类和聚类注释。
