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A Baseline Correction for Effective Analysis of Alzheimer’s Disease based on Raman Spectra from Platelet  

Park, Aa-Ron (The School of Electronic and Computer Engineering, Chonnam National University)
Baek, Sung-June (The School of Electronic and Computer Engineering, Chonnam National University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea CI / v.49, no.1, 2012 , pp. 16-22 More about this Journal
Abstract
In this paper, we proposed a method of baseline correction for analysis of Raman spectra of platelets from Alzheimer's disease (AD) transgenic mice. Measured Raman spectra include the meaningful information and unnecessary noise which is composed of baseline and additive noise. The Raman spectrum is divided into the local region including several peaks and the spectrum of the region is modeled by curve fitting using Gaussian model. The additive noise is clearly removed from the process of replacing the original spectrum with the fitted model. The baseline correction after interpolating the local minima of the fitted model with linear, piecewise cubic Hermite and cubic spline algorithm. The baseline corrected models extract the feature with principal component analysis (PCA). The classification result of support vector machine (SVM) and maximum $a$ posteriori probability (MAP) using linear interpolation method showed the good performance about overall number of principal components, especially SVM gave the best performance which is about 97.3% true classification average rate in case of piecewise cubic Hermite algorithm and 5 principal components. In addition, it confirmed that the proposed baseline correction method compared with the previous research result could be effectively applied in the analysis of the Raman spectra of platelet.
Keywords
baseline correction; denoising; smoothing; curve fitting; Raman spectroscopy;
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