KEYWORDS: Raman spectroscopy, Small targets, Biological samples, Systems modeling, Spectrometers, Time metrology, Support vector machines, Statistical modeling, Principal component analysis, Neural networks
Two main obstacles preventing widespread use of Raman spectroscopy in medical fields are slow acquisition times and poor classification model transferability. We present techniques for improving data acquisition using minimal sampling or other modalities for rapid pre-screening and an area based dimension reduction technique with improved transferability. We illustrate the strengths and weaknesses of these methods in comparison with common practices. Our investigation is based on microplastic samples. While these samples are not biological, they model problems Raman spectroscopy faces in the medical field on a stable time scale, allowing many measurements for detailed analysis of methods.
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