RamanLIGHT—a graphical user-friendly tool for pre-processing and unmixing hyperspectral Raman spectroscopy images. (1st June 2022)

• Record Type: Journal Article
• Authors: Schmidt, Robert W; Woutersen, Sander; Ariese, Freek
• Is Part Of: Journal of optics. Volume 24:Number 6(2022)
• Publication Date: 2022-06-01
• Subjects: Raman spectroscopy -- hyperspectral imaging -- unsupervised unmixing -- multivariate analysis; Optics -- Periodicals; 535.05
• DOI: 10.1088/2040-8986/ac6883
• Languages: English
• ISSNs: 2040-8978

Abstract

Abstract: Raman spectroscopy is a valuable tool for non-destructive vibrational analysis of chemical compounds in various samples. Through 2D scanning, it one can map the chemical surface distribution in a heterogeneous sample. These hyperspectral Raman images typically contain spectra of pure compounds that are hidden within thousands of sum spectra. Inspecting each spectrum to find the pure compounds in the dataset is impractical, and several algorithms have been described in the literature to help analyze such complex datasets. However, choosing the best approach(es) and optimizing the parameters is often difficult, and the necessary software was not yet combined in a single program. Therefore, we introduce RamanLIGHT, a fast and simple app to pre-process Raman mapping datasets and apply up to eight unsupervised unmixing algorithms to find endmember spectra of pure compounds. The user can select from six smoothing methods, four fluorescence baseline-removal methods, four normalization methods, and cosmic-ray and outlier removal to generate a uniform dataset prior to the unmixing. We included the most promising pre-processing methods, since there is no routine that perfectly fits all types of samples. Unmixed endmember spectra can be further used to visualize the distribution of compounds in a sample by creating abundance maps for each endmember separately, or a single labeled image containing all endmembers. It is also possible to create a mean spectrum for each endmember, which better describes the true compound spectrum. We tested RamanLIGHT on three samples: an aspirin-paracetamol-caffeine tablet, Alzheimer's disease brain tissue and a phase-separated polymer coating. The datasets were pre-processed and unmixed within seconds to gain endmembers of known and unknown chemical compounds. The unmixing algorithms are sensitive to noisy spectra and strong fluorescence backgrounds, so it is important to apply pre-processing methods to a suitable degree. RamanLIGHT is freely available as an MATLAB and soon as standalone app.