Spectroscopic apparatus and methods
View Patent ↗A method of estimating background radiation in spectral data. The method may comprise, iteratively, fitting an analytical curve, such as a spline curve, to reference data, determining an allowable deviation of the reference data from the analytical curve and clipping data points of the reference data or the spectral data that are more than the allowable deviation above the analytical curve to provide the reference data for the next iteration until termination criterion is met. The reference data is initially based upon the spectral data. The method may comprise generating estimates of background radiation of the spectral data, each estimate based upon fitting a different order polynomial to the spectral data, and selecting an order of polynomial to use for estimating background radiation and/or one of the estimates of the background radiation. The method may further comprise estimating the noise in the spectral data from the reference data.
1. A method for automatically estimating background in spectral data, the method comprising:
receiving spectral data captured by a Raman spectroscopy apparatus, the spectral data comprising a Raman spectrum together with a background signal;
carrying out an iterative process comprised of an initial iteration and a subsequent iteration, the initial iteration comprising (i) fitting an analytical curve to initial reference data based upon the received spectral data, (ii) determining an allowable deviation of the initial reference data from the analytical curve, and (iii) removing data points of the initial reference data or the spectral data that are more than the allowable deviation above the analytical curve to provide subsequent reference data, and each subsequent iteration comprising (i) fitting an analytical curve to the subsequent reference data, (ii) determining an allowable deviation of the subsequent reference data from the analytical curve, and (iii) removing data points of the subsequent reference data or the spectral data that are more than the allowable deviation above the analytical curve to provide reference data, wherein the reference data is used as the subsequent reference data in a next subsequent iteration of the iterative process unless termination criterion is met; and
outputting an estimate of the background signal in the spectral data based upon the reference data or the analytical curve refined by the iterative process.
2. A method according to claim 1 , wherein the analytical curve is a polynomial.
3. A method according to claim 1 , wherein the analytical curve is a spline curve.
4. Apparatus comprising a processor arranged to perform the method according to claim 1 .
5. A data carrier having instructions thereon, which, when executed by a processor, cause the processor to carry out the method of claim 1 .
6. A method according to claim 1 , comprising outputting the estimate of the background signal in the spectral data based upon the reference data or the analytical curve determined by the final iteration of the iterative process.
7. A method of identifying components present in a sample, the method comprising:
carrying out Raman spectroscopy on the sample to obtain spectral data;
carrying out the method of claim 1 on the spectral data to determine an estimate of background radiation in the spectral data;
generating modified spectral data by removing data points based upon the estimate of background radiation; and
identifying at least one component present in the sample by analysing the modified spectral data to identify a spectral signal indicative of the at least one component.
8. A method according to claim 2 , wherein the allowable deviation is based upon an average deviation of the reference data from the polynomial.
9. A method according to claim 2 , wherein the allowable deviation is based upon an estimate of noise.
10. A method according to claim 2 , comprising estimating noise in the spectral data from the reference data.
11. A method according to claim 2 , wherein the termination criterion is met when no removing occurs in an iteration.
12. A method according to claim 2 , wherein the termination criterion is met when a set number of iterations are carried out.
13. A method according to claim 2 , comprising determining an order of polynomial to fit to the reference data.
14. A method according to claim 3 , wherein the spline curve is a cubic spline.
15. A method according to claim 3 , comprising fitting a spline curve to the reference data using a predefined number of anchor points.
16. A method according to claim 3 , wherein the number of anchor points is predefined based on the resolution of the spectroscopy apparatus used to obtain the spectral data.
17. A method according to claim 3 , wherein the number of anchor points is predefined based on a likely width of the Raman peaks.
18. A method according to claim 3 , wherein fitting of the spline curve comprises identifying a location of anchors.
19. A method according to claim 3 , wherein the allowable deviation is based upon an average deviation of the reference data from the spline curve.
20. A method according to claim 3 , wherein the allowable deviation is based upon a root mean square, RMS, of the reference data from the spline curve.
21. A method according to claim 3 , wherein the allowable deviation is based upon an estimate of noise.
22. A method according to claim 3 , comprising estimating noise in the spectral data from the reference data.
23. A method according to claim 3 , wherein the termination criterion is met when no removing occurs in an iteration.
24. A method according to claim 23 , wherein the termination criterion is met when a set number of iterations are carried out.
25. A method according to claim 3 , wherein the termination criterion is met when a set number of iterations are carried out.
26. A method according to claim 3 , comprising determining an order of spline curve to fit to the reference data.
27. A method according to claim 8 , wherein the allowable deviation is based upon a root mean square, RMS, of the reference data from the polynomial.
28. A method according to claim 8 , wherein the allowable deviation is a multiple, M, of the average deviation.
29. A method according to claim 9 , wherein the estimate of noise is based upon an average variation between each point of the reference data.
30. A method according to claim 9 , wherein the estimate of noise is based upon a deviation of the reference data from the polynomial/estimate of background radiation.
31. A method according to claim 9 , comprising making an estimate of noise using the reference data provided by a final iteration.
32. A method according to claim 11 , wherein the termination criterion is met when a set number of iterations are carried out.
33. A method according to claim 15 , wherein the method is computer implemented and the number of anchor points is predefined by a user.
34. A method according to claim 18 , wherein the locations of the anchors for each iteration are identified automatically using an algorithm.
35. A method according to claim 19 , wherein the allowable deviation is a multiple, M, of the average deviation.
36. A method according to claim 22 , wherein the estimate of noise is based upon an average variation between each point of the reference data.
37. A method according to claim 22 , wherein the estimate of noise is based upon a deviation of the reference data from the spline curve/estimate of background radiation.
38. A method according to claim 22 , comprising making an estimate of noise using the reference data provided by a final iteration.