Method for obtaining true Raman spectrum of cell by multiple linear regression fitting

Abstract

The invention discloses a method for obtaining a true Raman spectrum of a cell by multiple linear regression fitting. The method comprises the following steps: acquiring the original Raman spectrum of the cell; acquiring a smooth Raman spectrum after smoothing; acquiring primitive-variable Raman spectrums of all primitive variables in the cell; initially fitting and calculating an approximate fluorescence background Raman spectrum of the cell; obtaining a fitting coefficient corresponding to each primitive variable and background variable by multiple linear regression fitting; finally determining the fluorescence background Raman spectrum of the cell by the sum of products of the background variable Raman spectrums and corresponding fitting coefficients; deducting the obtained fluorescence background Raman spectrum by using smoothing Raman spectrum and obtaining the true Raman spectrum of the cell. The method disclosed by the invention is used for eliminating the background fluorescence of the Raman spectrum of the cell, can fit out the fluorescence background of the Raman spectrum of the cell more accurately than other methods, and can realize fast elimination of the fluorescence background of the Raman spectrum of the cell so as to obtain the true Raman spectrum of the cell.

Description

technical field [0001] The invention relates to the field of cell optical measurement, in particular to a method for obtaining real cell Raman spectra through multiple linear regression fitting. Background technique [0002] Raman spectroscopy can quantitatively analyze the composition and composition of cells, providing a large amount of information about a large number of biological macromolecules such as proteins, nucleic acids, lipids, and glycogen that make up cells, and can monitor cells in real time without damaging cells. Changes in molecular structure. Then, the background noise, especially the fluorescence background noise, is very large when performing cell Raman spectroscopy measurements. How to effectively eliminate fluorescent back sound has always been one of the difficult problems to be solved in the application research of Raman spectroscopy. The current methods for eliminating cell Raman fluorescence background include: least square algorithm, polynomial ...

AI Technical Summary

Problems solved by technology

The above method uses the intensity distribution profile of the cell Raman spectrum and combines the spectral features to fit the fluorescence background. After verification, the cell Raman spectra obtained by the above method are quite different, indicating that the current fluorescence background estimation method has a large error.

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