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Method for Removing Spectral Contaminants to Improve Analysis of Raman Imaging Data
The spectral contaminants are inevitable during micro-Raman measurements. A key challenge is how to remove them from the original imaging data, since they can distort further results of data analysis. Here, we propose a method named “automatic pre-processing method for Raman imaging data set (APRI)”...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5215229/ https://www.ncbi.nlm.nih.gov/pubmed/28054587 http://dx.doi.org/10.1038/srep39891 |
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author | Zhang, Xun Chen, Sheng Ling, Zhe Zhou, Xia Ding, Da-Yong Kim, Yoon Soo Xu, Feng |
author_facet | Zhang, Xun Chen, Sheng Ling, Zhe Zhou, Xia Ding, Da-Yong Kim, Yoon Soo Xu, Feng |
author_sort | Zhang, Xun |
collection | PubMed |
description | The spectral contaminants are inevitable during micro-Raman measurements. A key challenge is how to remove them from the original imaging data, since they can distort further results of data analysis. Here, we propose a method named “automatic pre-processing method for Raman imaging data set (APRI)”, which includes the adaptive iteratively reweighted penalized least-squares (airPLS) algorithm and the principal component analysis (PCA). It eliminates the baseline drifts and cosmic spikes by using the spectral features themselves. The utility of APRI is illustrated by removing the spectral contaminants from a Raman imaging data set of a wood sample. In addition, APRI is computationally efficient, conceptually simple and potential to be extended to other methods of spectroscopy, such as infrared (IR), nuclear magnetic resonance (NMR), X-Ray Diffraction (XRD). With the help of our approach, a typical spectral analysis can be performed by a non-specialist user to obtain useful information from a spectroscopic imaging data set. |
format | Online Article Text |
id | pubmed-5215229 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-52152292017-01-09 Method for Removing Spectral Contaminants to Improve Analysis of Raman Imaging Data Zhang, Xun Chen, Sheng Ling, Zhe Zhou, Xia Ding, Da-Yong Kim, Yoon Soo Xu, Feng Sci Rep Article The spectral contaminants are inevitable during micro-Raman measurements. A key challenge is how to remove them from the original imaging data, since they can distort further results of data analysis. Here, we propose a method named “automatic pre-processing method for Raman imaging data set (APRI)”, which includes the adaptive iteratively reweighted penalized least-squares (airPLS) algorithm and the principal component analysis (PCA). It eliminates the baseline drifts and cosmic spikes by using the spectral features themselves. The utility of APRI is illustrated by removing the spectral contaminants from a Raman imaging data set of a wood sample. In addition, APRI is computationally efficient, conceptually simple and potential to be extended to other methods of spectroscopy, such as infrared (IR), nuclear magnetic resonance (NMR), X-Ray Diffraction (XRD). With the help of our approach, a typical spectral analysis can be performed by a non-specialist user to obtain useful information from a spectroscopic imaging data set. Nature Publishing Group 2017-01-05 /pmc/articles/PMC5215229/ /pubmed/28054587 http://dx.doi.org/10.1038/srep39891 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Zhang, Xun Chen, Sheng Ling, Zhe Zhou, Xia Ding, Da-Yong Kim, Yoon Soo Xu, Feng Method for Removing Spectral Contaminants to Improve Analysis of Raman Imaging Data |
title | Method for Removing Spectral Contaminants to Improve Analysis of Raman Imaging Data |
title_full | Method for Removing Spectral Contaminants to Improve Analysis of Raman Imaging Data |
title_fullStr | Method for Removing Spectral Contaminants to Improve Analysis of Raman Imaging Data |
title_full_unstemmed | Method for Removing Spectral Contaminants to Improve Analysis of Raman Imaging Data |
title_short | Method for Removing Spectral Contaminants to Improve Analysis of Raman Imaging Data |
title_sort | method for removing spectral contaminants to improve analysis of raman imaging data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5215229/ https://www.ncbi.nlm.nih.gov/pubmed/28054587 http://dx.doi.org/10.1038/srep39891 |
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