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In Raman-based diagnostic applications, principal component analysis (PCA) has often been used to distinguish different cell types or abnormalities. The performance of PCA greatly depends on the baseline adjustment of the measured spectra. Hence, the effect of erroneous baseline fitting on PCA requires to be addressed. Thus, we investigate the impact of baseline error for Raman spectra on PCA through the application of polynomial function with different orders in the fingerprint region (~600-1800cm-1). We found that the third order polynomial baseline fitting generated the fitted spectra closest to the mean spectrum and provided more precise PCA results.
Kaustav Das,Terumasa Ito, andKazuhiko Misawa
"Investigation on baseline fitting for Raman spectroscopy of living cells and its impact on principal component analysis", Proc. SPIE PC12363, Multiscale Imaging and Spectroscopy IV, PC1236307 (17 March 2023); https://doi.org/10.1117/12.2649537
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Kaustav Das, Terumasa Ito, Kazuhiko Misawa, "Investigation on baseline fitting for Raman spectroscopy of living cells and its impact on principal component analysis," Proc. SPIE PC12363, Multiscale Imaging and Spectroscopy IV, PC1236307 (17 March 2023); https://doi.org/10.1117/12.2649537