期刊
APPLIED SPECTROSCOPY
卷 72, 期 9, 页码 1322-1340出版社
SAGE PUBLICATIONS INC
DOI: 10.1177/0003702818778031
关键词
Raman spectroscopy; mammalian cells; fully automated preprocessing; preprocessing quality control; baseline correction; cosmic ray spike removal; smoothing; quality factor; quality parameter
资金
- Natural Sciences and Engineering Research Council of Canada
- Canadian Institutes of Health Research, under the Collaborative Health Research Projects Program
- Canadian Foundation for Innovation
- British Columbia Knowledge Development Foundation
Spectral preprocessing is frequently required to render Raman spectra useful for further processing and analyses. The various preprocessing steps, individually and sequentially, are increasingly being automated to cope with large volumes of data from, for example, hyperspectral imaging studies. Full automation of preprocessing is especially desirable when it produces consistent results and requires minimal user input. It is therefore essential to evaluate the quality of such preprocessed spectra. However, relatively few methods exist to evaluate preprocessing quality, and fully automated methods for doing so are virtually non-existent. Here we provide a brief overview of fully automated spectral preprocessing and fully automated quality assessment of preprocessed spectra. We follow this with the introduction of fully automated methods to establish figures-of-merit that encapsulate preprocessing quality. By way of illustration, these quantitative methods are applied to simulated and real Raman spectra. Quality factor and quality parameter figures-of-merit resulting from individual preprocessing step quality tests, as well as overall figures-of-merit, were found to be consistent with the quality of preprocessed spectra.
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