Loading…

Generation of Raman images through spectral mappings

In this work, we propose a practical approach to access and visualize relevant information on the spatial distribution on the anything sample about its biochemical composition. In order to carry out this analysis, we use a Raman spectroscopy technique to obtain spectral maps with specific spatial re...

Full description

Saved in:
Bibliographic Details
Published in:Journal of intelligent & fuzzy systems 2019-01, Vol.36 (5), p.4991-4999
Main Authors: Martínez-Espinosa, J.C., Cordova-Fraga, T., Guzmán-Cabrera, R.
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites cdi_FETCH-LOGICAL-c219t-cc4f6f43153a2c317f2a44b5e9fae245613120c5c1645ca7d329d017d1f3babe3
container_end_page 4999
container_issue 5
container_start_page 4991
container_title Journal of intelligent & fuzzy systems
container_volume 36
creator Martínez-Espinosa, J.C.
Cordova-Fraga, T.
Guzmán-Cabrera, R.
description In this work, we propose a practical approach to access and visualize relevant information on the spatial distribution on the anything sample about its biochemical composition. In order to carry out this analysis, we use a Raman spectroscopy technique to obtain spectral maps with specific spatial resolution (1 and 5 micrometers) over a selected region of the sample. Our study relies on the application of a Principal Component Analysis on the cross-correlations between the spectral blocks measured, within a certain spectral window of interest. The associated values of these principal components are used to build low-resolution images (with the same spatial resolution of the Raman scan) in which the relevant information on the chemical composition is already encoded. Finally, the spatial resolution of the principal components images was numerically enhanced in the post-processing through standard linear interpolation algorithms. In this way, we can map and visualize, simultaneously, the spatial and spectral information. The results suggest that the Raman spectroscopy imaging is a powerful tool for determining the biochemistry of organic and inorganic samples based on spectral scanning and thus determine compounds concentrations of medical interest. The proposed methodology is rather general and it could be extended to other spectroscopic measurement techniques where the spatial mapping of the spectral information is needed.
doi_str_mv 10.3233/JIFS-179045
format article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2224401948</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2224401948</sourcerecordid><originalsourceid>FETCH-LOGICAL-c219t-cc4f6f43153a2c317f2a44b5e9fae245613120c5c1645ca7d329d017d1f3babe3</originalsourceid><addsrcrecordid>eNotkMtOwzAQRS0EEqWw4gcisUQGjz1O4iWqaCmqhMRjbTmOnaZqHtjJgr9vqrCaWRzdO3MIuQf2JLgQz-_b9ReFTDGUF2QBeSZprtLsctpZihQ4ptfkJsYDY5BJzhYEN651wQx11yadTz5NY9qkbkzlYjLsQzdW-yT2zg7BHJPG9H3dVvGWXHlzjO7ufy7Jz_r1e_VGdx-b7eplRy0HNVBr0aceBUhhuBWQeW4QC-mUN46jTEEAZ1ZaSFFak5WCq3I6rAQvClM4sSQPc24fut_RxUEfujG0U6XmnCMyUJhP1ONM2dDFGJzXfZg-CH8amD5r0WctetYiTg2sU_A</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2224401948</pqid></control><display><type>article</type><title>Generation of Raman images through spectral mappings</title><source>Business Source Ultimate</source><creator>Martínez-Espinosa, J.C. ; Cordova-Fraga, T. ; Guzmán-Cabrera, R.</creator><contributor>Singh, Vivek ; Pinto, David</contributor><creatorcontrib>Martínez-Espinosa, J.C. ; Cordova-Fraga, T. ; Guzmán-Cabrera, R. ; Singh, Vivek ; Pinto, David</creatorcontrib><description>In this work, we propose a practical approach to access and visualize relevant information on the spatial distribution on the anything sample about its biochemical composition. In order to carry out this analysis, we use a Raman spectroscopy technique to obtain spectral maps with specific spatial resolution (1 and 5 micrometers) over a selected region of the sample. Our study relies on the application of a Principal Component Analysis on the cross-correlations between the spectral blocks measured, within a certain spectral window of interest. The associated values of these principal components are used to build low-resolution images (with the same spatial resolution of the Raman scan) in which the relevant information on the chemical composition is already encoded. Finally, the spatial resolution of the principal components images was numerically enhanced in the post-processing through standard linear interpolation algorithms. In this way, we can map and visualize, simultaneously, the spatial and spectral information. The results suggest that the Raman spectroscopy imaging is a powerful tool for determining the biochemistry of organic and inorganic samples based on spectral scanning and thus determine compounds concentrations of medical interest. The proposed methodology is rather general and it could be extended to other spectroscopic measurement techniques where the spatial mapping of the spectral information is needed.</description><identifier>ISSN: 1064-1246</identifier><identifier>EISSN: 1875-8967</identifier><identifier>DOI: 10.3233/JIFS-179045</identifier><language>eng</language><publisher>Amsterdam: IOS Press BV</publisher><subject>Algorithms ; Chemical composition ; Coding ; Correlation analysis ; Image enhancement ; Image resolution ; Interpolation ; Mapping ; Measurement techniques ; Micrometers ; Organic chemistry ; Post-processing ; Principal components analysis ; Raman spectroscopy ; Spatial distribution ; Spatial resolution ; Spectra ; Spectrum analysis</subject><ispartof>Journal of intelligent &amp; fuzzy systems, 2019-01, Vol.36 (5), p.4991-4999</ispartof><rights>Copyright IOS Press BV 2019</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c219t-cc4f6f43153a2c317f2a44b5e9fae245613120c5c1645ca7d329d017d1f3babe3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,777,781,27905,27906</link.rule.ids></links><search><contributor>Singh, Vivek</contributor><contributor>Pinto, David</contributor><creatorcontrib>Martínez-Espinosa, J.C.</creatorcontrib><creatorcontrib>Cordova-Fraga, T.</creatorcontrib><creatorcontrib>Guzmán-Cabrera, R.</creatorcontrib><title>Generation of Raman images through spectral mappings</title><title>Journal of intelligent &amp; fuzzy systems</title><description>In this work, we propose a practical approach to access and visualize relevant information on the spatial distribution on the anything sample about its biochemical composition. In order to carry out this analysis, we use a Raman spectroscopy technique to obtain spectral maps with specific spatial resolution (1 and 5 micrometers) over a selected region of the sample. Our study relies on the application of a Principal Component Analysis on the cross-correlations between the spectral blocks measured, within a certain spectral window of interest. The associated values of these principal components are used to build low-resolution images (with the same spatial resolution of the Raman scan) in which the relevant information on the chemical composition is already encoded. Finally, the spatial resolution of the principal components images was numerically enhanced in the post-processing through standard linear interpolation algorithms. In this way, we can map and visualize, simultaneously, the spatial and spectral information. The results suggest that the Raman spectroscopy imaging is a powerful tool for determining the biochemistry of organic and inorganic samples based on spectral scanning and thus determine compounds concentrations of medical interest. The proposed methodology is rather general and it could be extended to other spectroscopic measurement techniques where the spatial mapping of the spectral information is needed.</description><subject>Algorithms</subject><subject>Chemical composition</subject><subject>Coding</subject><subject>Correlation analysis</subject><subject>Image enhancement</subject><subject>Image resolution</subject><subject>Interpolation</subject><subject>Mapping</subject><subject>Measurement techniques</subject><subject>Micrometers</subject><subject>Organic chemistry</subject><subject>Post-processing</subject><subject>Principal components analysis</subject><subject>Raman spectroscopy</subject><subject>Spatial distribution</subject><subject>Spatial resolution</subject><subject>Spectra</subject><subject>Spectrum analysis</subject><issn>1064-1246</issn><issn>1875-8967</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNotkMtOwzAQRS0EEqWw4gcisUQGjz1O4iWqaCmqhMRjbTmOnaZqHtjJgr9vqrCaWRzdO3MIuQf2JLgQz-_b9ReFTDGUF2QBeSZprtLsctpZihQ4ptfkJsYDY5BJzhYEN651wQx11yadTz5NY9qkbkzlYjLsQzdW-yT2zg7BHJPG9H3dVvGWXHlzjO7ufy7Jz_r1e_VGdx-b7eplRy0HNVBr0aceBUhhuBWQeW4QC-mUN46jTEEAZ1ZaSFFak5WCq3I6rAQvClM4sSQPc24fut_RxUEfujG0U6XmnCMyUJhP1ONM2dDFGJzXfZg-CH8amD5r0WctetYiTg2sU_A</recordid><startdate>20190101</startdate><enddate>20190101</enddate><creator>Martínez-Espinosa, J.C.</creator><creator>Cordova-Fraga, T.</creator><creator>Guzmán-Cabrera, R.</creator><general>IOS Press BV</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20190101</creationdate><title>Generation of Raman images through spectral mappings</title><author>Martínez-Espinosa, J.C. ; Cordova-Fraga, T. ; Guzmán-Cabrera, R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c219t-cc4f6f43153a2c317f2a44b5e9fae245613120c5c1645ca7d329d017d1f3babe3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Algorithms</topic><topic>Chemical composition</topic><topic>Coding</topic><topic>Correlation analysis</topic><topic>Image enhancement</topic><topic>Image resolution</topic><topic>Interpolation</topic><topic>Mapping</topic><topic>Measurement techniques</topic><topic>Micrometers</topic><topic>Organic chemistry</topic><topic>Post-processing</topic><topic>Principal components analysis</topic><topic>Raman spectroscopy</topic><topic>Spatial distribution</topic><topic>Spatial resolution</topic><topic>Spectra</topic><topic>Spectrum analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Martínez-Espinosa, J.C.</creatorcontrib><creatorcontrib>Cordova-Fraga, T.</creatorcontrib><creatorcontrib>Guzmán-Cabrera, R.</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Journal of intelligent &amp; fuzzy systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Martínez-Espinosa, J.C.</au><au>Cordova-Fraga, T.</au><au>Guzmán-Cabrera, R.</au><au>Singh, Vivek</au><au>Pinto, David</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Generation of Raman images through spectral mappings</atitle><jtitle>Journal of intelligent &amp; fuzzy systems</jtitle><date>2019-01-01</date><risdate>2019</risdate><volume>36</volume><issue>5</issue><spage>4991</spage><epage>4999</epage><pages>4991-4999</pages><issn>1064-1246</issn><eissn>1875-8967</eissn><abstract>In this work, we propose a practical approach to access and visualize relevant information on the spatial distribution on the anything sample about its biochemical composition. In order to carry out this analysis, we use a Raman spectroscopy technique to obtain spectral maps with specific spatial resolution (1 and 5 micrometers) over a selected region of the sample. Our study relies on the application of a Principal Component Analysis on the cross-correlations between the spectral blocks measured, within a certain spectral window of interest. The associated values of these principal components are used to build low-resolution images (with the same spatial resolution of the Raman scan) in which the relevant information on the chemical composition is already encoded. Finally, the spatial resolution of the principal components images was numerically enhanced in the post-processing through standard linear interpolation algorithms. In this way, we can map and visualize, simultaneously, the spatial and spectral information. The results suggest that the Raman spectroscopy imaging is a powerful tool for determining the biochemistry of organic and inorganic samples based on spectral scanning and thus determine compounds concentrations of medical interest. The proposed methodology is rather general and it could be extended to other spectroscopic measurement techniques where the spatial mapping of the spectral information is needed.</abstract><cop>Amsterdam</cop><pub>IOS Press BV</pub><doi>10.3233/JIFS-179045</doi><tpages>9</tpages></addata></record>
fulltext fulltext
identifier ISSN: 1064-1246
ispartof Journal of intelligent & fuzzy systems, 2019-01, Vol.36 (5), p.4991-4999
issn 1064-1246
1875-8967
language eng
recordid cdi_proquest_journals_2224401948
source Business Source Ultimate
subjects Algorithms
Chemical composition
Coding
Correlation analysis
Image enhancement
Image resolution
Interpolation
Mapping
Measurement techniques
Micrometers
Organic chemistry
Post-processing
Principal components analysis
Raman spectroscopy
Spatial distribution
Spatial resolution
Spectra
Spectrum analysis
title Generation of Raman images through spectral mappings
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-18T22%3A03%3A02IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Generation%20of%20Raman%20images%20through%20spectral%20mappings&rft.jtitle=Journal%20of%20intelligent%20&%20fuzzy%20systems&rft.au=Mart%C3%ADnez-Espinosa,%20J.C.&rft.date=2019-01-01&rft.volume=36&rft.issue=5&rft.spage=4991&rft.epage=4999&rft.pages=4991-4999&rft.issn=1064-1246&rft.eissn=1875-8967&rft_id=info:doi/10.3233/JIFS-179045&rft_dat=%3Cproquest_cross%3E2224401948%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c219t-cc4f6f43153a2c317f2a44b5e9fae245613120c5c1645ca7d329d017d1f3babe3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2224401948&rft_id=info:pmid/&rfr_iscdi=true