Automated quantitative analysis of MCC-IMS spectra

Detalhes bibliográficos
Autor(a) principal: Alho, Luís Miguel Pereira Domingues
Data de Publicação: 2014
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/14959
Resumo: Ion Mobility Spectrometry coupled with Multi Capillary Columns (MCC -IMS) is a fast analytical technique working at atmospheric pressure with high sensitivity and selectivity making it suitable for the analysis of complex biological matrices. MCC-IMS analysis generates its information through a 3D spectrum with peaks, corresponding to each of the substances detected, providing quantitative and qualitative information. Sometimes peaks of different substances overlap, making the quantification of substances present in the biological matrices a difficult process. In the present work we use peaks of isoprene and acetone as a model for this problem. These two volatile organic compounds (VOCs) that when detected by MCC-IMS produce two overlapping peaks. In this work it’s proposed an algorithm to identify and quantify these two peaks. This algorithm uses image processing techniques to treat the spectra and to detect the position of the peaks, and then fits the data to a custom model in order to separate the peaks. Once the peaks are separated it calculates the contribution of each peak to the data.
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spelling Automated quantitative analysis of MCC-IMS spectraIon Mobility Spectrometry (IMS)Multicapillary columns (MCC)Image processingVolatile Organic Compounds (VOCs)QuantificationSurface fittingIon Mobility Spectrometry coupled with Multi Capillary Columns (MCC -IMS) is a fast analytical technique working at atmospheric pressure with high sensitivity and selectivity making it suitable for the analysis of complex biological matrices. MCC-IMS analysis generates its information through a 3D spectrum with peaks, corresponding to each of the substances detected, providing quantitative and qualitative information. Sometimes peaks of different substances overlap, making the quantification of substances present in the biological matrices a difficult process. In the present work we use peaks of isoprene and acetone as a model for this problem. These two volatile organic compounds (VOCs) that when detected by MCC-IMS produce two overlapping peaks. In this work it’s proposed an algorithm to identify and quantify these two peaks. This algorithm uses image processing techniques to treat the spectra and to detect the position of the peaks, and then fits the data to a custom model in order to separate the peaks. Once the peaks are separated it calculates the contribution of each peak to the data.Vassilenko, ValentinaMora, AndréRUNAlho, Luís Miguel Pereira Domingues2015-05-14T14:10:37Z2014-092015-052014-09-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/14959enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T03:50:26Zoai:run.unl.pt:10362/14959Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:22:12.547055Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Automated quantitative analysis of MCC-IMS spectra
title Automated quantitative analysis of MCC-IMS spectra
spellingShingle Automated quantitative analysis of MCC-IMS spectra
Alho, Luís Miguel Pereira Domingues
Ion Mobility Spectrometry (IMS)
Multicapillary columns (MCC)
Image processing
Volatile Organic Compounds (VOCs)
Quantification
Surface fitting
title_short Automated quantitative analysis of MCC-IMS spectra
title_full Automated quantitative analysis of MCC-IMS spectra
title_fullStr Automated quantitative analysis of MCC-IMS spectra
title_full_unstemmed Automated quantitative analysis of MCC-IMS spectra
title_sort Automated quantitative analysis of MCC-IMS spectra
author Alho, Luís Miguel Pereira Domingues
author_facet Alho, Luís Miguel Pereira Domingues
author_role author
dc.contributor.none.fl_str_mv Vassilenko, Valentina
Mora, André
RUN
dc.contributor.author.fl_str_mv Alho, Luís Miguel Pereira Domingues
dc.subject.por.fl_str_mv Ion Mobility Spectrometry (IMS)
Multicapillary columns (MCC)
Image processing
Volatile Organic Compounds (VOCs)
Quantification
Surface fitting
topic Ion Mobility Spectrometry (IMS)
Multicapillary columns (MCC)
Image processing
Volatile Organic Compounds (VOCs)
Quantification
Surface fitting
description Ion Mobility Spectrometry coupled with Multi Capillary Columns (MCC -IMS) is a fast analytical technique working at atmospheric pressure with high sensitivity and selectivity making it suitable for the analysis of complex biological matrices. MCC-IMS analysis generates its information through a 3D spectrum with peaks, corresponding to each of the substances detected, providing quantitative and qualitative information. Sometimes peaks of different substances overlap, making the quantification of substances present in the biological matrices a difficult process. In the present work we use peaks of isoprene and acetone as a model for this problem. These two volatile organic compounds (VOCs) that when detected by MCC-IMS produce two overlapping peaks. In this work it’s proposed an algorithm to identify and quantify these two peaks. This algorithm uses image processing techniques to treat the spectra and to detect the position of the peaks, and then fits the data to a custom model in order to separate the peaks. Once the peaks are separated it calculates the contribution of each peak to the data.
publishDate 2014
dc.date.none.fl_str_mv 2014-09
2014-09-01T00:00:00Z
2015-05-14T14:10:37Z
2015-05
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/14959
url http://hdl.handle.net/10362/14959
dc.language.iso.fl_str_mv eng
language eng
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eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
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instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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