Baseline correction noise

In this section, we present the development of an automated protocol for prostate tissue histology [164] from infrared spectroscopic imaging data as an example of the techniques described (Fig. 8.11). The data is three dimensional with x-y—axes representing the image plane and the 2-axis representing the spectral dimension. After data acquisition, two important pre-processing steps, namely baseline correction and de-noising, are performed. Since the entire data set is derived from human tissue samples, the spectra have similar characteristics and, therefore, a manually chosen set of pre-defined wave number could be used as the reference points for baseline correction. It is... 

If the leakage flux falls within the acceptable range we merely measure its value for use as a baseline correction to the pressure vs time data taken when the upstream chamber is pressurized. The presence of this background flux tends to degrade the signal to noise ratio of the data for the less permeable species. Experiments using a solid aluminum plate in place of the film demonstrate that this leakage flux arises mainly from the polymer. 

Use baseline corrections on each integral cut if spectral tilt is noticeable. Extensive zero filling (see step 2) is useful, because it provides more data points to define line shapes better (Section 2-5b). Slight line broadening produces smoother spectral and integral lines with less baseline noise. 

The signal quality (= low detector noise) and sample rate should be sufficiently high to obtain correct results, otherwise post processing of the data is necessary, such as smoothing, baseline correction, etc. Even then the result of the integration in Eq. 6.126 depends very much on the extension of the baseline, and the obtained value of the second moment can be very inaccurate (Chapter 2.7, Section 6.5.3.3). 

Figu re 2.2 (a) Raw spectra of a Raman emulsion layer image (b) Spectra after de-noising by principal component analysis (PCA) (c) Spectra after de-noising and baseline correction by asymmetric least squares. 

A careful inspection of Equation 58 and Figure 9 leads to the following statement If a signal with linear drifting baseline and first order baseline noise is integrated, then the optimum baseline correction interval is infinite if the integration time is greater than four times the time constant of the noise otherwise, the optimum correction interval is zero. In the last case the use of two correction points on both sides of a peak is sufficient. 

The aim of baseline correction is to separate the analyte signal of interest from signal which arises due to changes in mobile phase composition or stationary phase bleed and signal due to electronic noise. Several baseline correction methods have been proposed in literature. 

Baseline correction, t noise reductions and related methods are found under this heading. Many concern NOE experiments in which difficulties concerning quantification are the most acute. Note two papers by Weiss and Ferretti and Weiss etal.- the first discusses accuracy and precision in the estimation of peak areas and NOE factors, and the second focuses on internuclear distances. Liu etal. also discussed the influence of experimental noise and peak integration errors on interproton distances. More recently, Lin et alJ simulated the influence of experimental imperfections on different kinds of experiments using gradients. 

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