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W idefield Raman Imaging of Cells and T issues   169


        simple baseline fits that correct for spectra containing a few Raman
        peaks. Often, with biological samples, the spectrum may be more
        complex, having a curving baseline. Multiple points and higher order
        polynomials may be chosen. Examples of this type of fit can be seen
        in Fig. 6.4. Here, a second order polynomial fit was used, and the
        points chosen for baseline fit included the first two points, the last
        two points, and a middle range of points encompassing the region
                          -1
        from 1810 to 2710 cm , where no Raman signal exists. The baseline fit
        is completed through construction of a polynomial model using a least-
        squares method. This model is applied to all pixels within the image by
        subtracting it from each spectrum. Figures 6.4a and b are the image and
        the average image spectrum pre-baseline correction, and the spec-
        trum after the baseline fit has been applied is seen in Fig. 6.4c.
            While this fit is effective and can be generally applied, this does
        have its disadvantages. It is not usually applied in real time, making
        Raman in vivo applications difficult, nor does it perform well in low
                         62
        SNR environments.  Current research into improving polynomial
        fits is being done to make the baseline fit procedure automated and
        account for low SNR data. 62,63
            Polynomial fitting is not the only methodology for baseline
        correction. Other common techniques utilize the first and sec-
        ond derivatives to correct for background fluorescence. The deriv-
        ative method is conducted using polynomial fits on small sections
        of the spectrum, where derivatives of the polynomial in the center
                                  56
        of the  section are calculated.  Similar to polynomial baseline fits;
        derivative-based techniques do not fit low-SNR data well.



                        2400
   Widefield Raman Image  2200         Pre-Baseline Corrected
     of Tissue 2930 cm –1              Post-Baseline Corrected
                        2000
                        1800
                      Intensity (a.u) 1600
                        1400
                        1200
                        1000
                        800
                        600   (b)
           (a)          400
                        200   (c)
                          0
                           600  900 1200  1500  1800  2100  2400 2700  3000
                                                    –1
                                        Raman Shift (cm )
   FIGURE 6.4  (a) Widefi eld Raman image of tissue and the average image spectrum
   (b) pre-baseline correction, (c) post-baseline correction.
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