Band-Target Entropy Minimization (BTEM) Applied to Hyperspectral Raman Image Data
Band-target entropy minimization (BTEM) has been applied to extraction of component spectra from hyperspectral Raman images. In this method singular value decomposition is used to calculate the eigenvectors of the spectroscopic image data set. Bands in non-noise eigenvectors that would normally be u...
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| Veröffentlicht in: | Applied spectroscopy 2003-11, Vol.57 (11), p.1353-1362 |
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| container_title | Applied spectroscopy |
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| creator | Widjaja, Effendi Crane, Nicole Chen, Tso-Ching Morris, Michael D. Ignelzi, Michael A. McCreadie, Barbara R. |
| description | Band-target entropy minimization (BTEM) has been applied to extraction of component spectra from hyperspectral Raman images. In this method singular value decomposition is used to calculate the eigenvectors of the spectroscopic image data set. Bands in non-noise eigenvectors that would normally be used for recovery of spectra are examined for localized spectral features. For a targeted (identified) band, information entropy minimization or a closely related algorithm is used to recover the spectrum containing this feature from the non-noise eigenvectors, plus the next 5–30 eigenvectors, in which noise predominates. Tests for which eigenvectors to include are described. The method is demonstrated on one synthesized Raman image data set and two bone tissue specimens. By inclusion of small amounts of signal that would be unused in other methods, BTEM enables the extraction of a larger number of component spectra than are otherwise obtainable. An improvement in signal/noise ratio of the recovered spectra is also obtained. |
| doi_str_mv | 10.1366/000370203322554509 |
| format | Article |
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In this method singular value decomposition is used to calculate the eigenvectors of the spectroscopic image data set. Bands in non-noise eigenvectors that would normally be used for recovery of spectra are examined for localized spectral features. For a targeted (identified) band, information entropy minimization or a closely related algorithm is used to recover the spectrum containing this feature from the non-noise eigenvectors, plus the next 5–30 eigenvectors, in which noise predominates. Tests for which eigenvectors to include are described. The method is demonstrated on one synthesized Raman image data set and two bone tissue specimens. By inclusion of small amounts of signal that would be unused in other methods, BTEM enables the extraction of a larger number of component spectra than are otherwise obtainable. An improvement in signal/noise ratio of the recovered spectra is also obtained.</description><identifier>ISSN: 0003-7028</identifier><identifier>EISSN: 1943-3530</identifier><identifier>DOI: 10.1366/000370203322554509</identifier><identifier>PMID: 14658148</identifier><language>eng</language><publisher>London, England: SAGE Publications</publisher><subject>Aged ; Algorithms ; Animals ; Computer Simulation ; Entropy ; Femur - chemistry ; Femur - pathology ; Humans ; Image Interpretation, Computer-Assisted - methods ; Male ; Mice ; Reproducibility of Results ; Sensitivity and Specificity ; Signal Processing, Computer-Assisted ; Skull - chemistry ; Skull - embryology ; Skull - pathology ; Spectrum Analysis, Raman - methods</subject><ispartof>Applied spectroscopy, 2003-11, Vol.57 (11), p.1353-1362</ispartof><rights>2003 Society for Applied Spectroscopy</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c405t-186cf7e77417a27d672db4f31e32de69ddf4ef6b227098994936326dabb954463</citedby><cites>FETCH-LOGICAL-c405t-186cf7e77417a27d672db4f31e32de69ddf4ef6b227098994936326dabb954463</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://journals.sagepub.com/doi/pdf/10.1366/000370203322554509$$EPDF$$P50$$Gsage$$H</linktopdf><linktohtml>$$Uhttps://journals.sagepub.com/doi/10.1366/000370203322554509$$EHTML$$P50$$Gsage$$H</linktohtml><link.rule.ids>314,776,780,21798,27901,27902,43597,43598</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/14658148$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Widjaja, Effendi</creatorcontrib><creatorcontrib>Crane, Nicole</creatorcontrib><creatorcontrib>Chen, Tso-Ching</creatorcontrib><creatorcontrib>Morris, Michael D.</creatorcontrib><creatorcontrib>Ignelzi, Michael A.</creatorcontrib><creatorcontrib>McCreadie, Barbara R.</creatorcontrib><title>Band-Target Entropy Minimization (BTEM) Applied to Hyperspectral Raman Image Data</title><title>Applied spectroscopy</title><addtitle>Appl Spectrosc</addtitle><description>Band-target entropy minimization (BTEM) has been applied to extraction of component spectra from hyperspectral Raman images. In this method singular value decomposition is used to calculate the eigenvectors of the spectroscopic image data set. Bands in non-noise eigenvectors that would normally be used for recovery of spectra are examined for localized spectral features. For a targeted (identified) band, information entropy minimization or a closely related algorithm is used to recover the spectrum containing this feature from the non-noise eigenvectors, plus the next 5–30 eigenvectors, in which noise predominates. Tests for which eigenvectors to include are described. The method is demonstrated on one synthesized Raman image data set and two bone tissue specimens. By inclusion of small amounts of signal that would be unused in other methods, BTEM enables the extraction of a larger number of component spectra than are otherwise obtainable. An improvement in signal/noise ratio of the recovered spectra is also obtained.</description><subject>Aged</subject><subject>Algorithms</subject><subject>Animals</subject><subject>Computer Simulation</subject><subject>Entropy</subject><subject>Femur - chemistry</subject><subject>Femur - pathology</subject><subject>Humans</subject><subject>Image Interpretation, Computer-Assisted - methods</subject><subject>Male</subject><subject>Mice</subject><subject>Reproducibility of Results</subject><subject>Sensitivity and Specificity</subject><subject>Signal Processing, Computer-Assisted</subject><subject>Skull - chemistry</subject><subject>Skull - embryology</subject><subject>Skull - pathology</subject><subject>Spectrum Analysis, Raman - methods</subject><issn>0003-7028</issn><issn>1943-3530</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2003</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kM1KAzEYRYMotlZfwIVkJboYm_9Mlm2tttAiSl0PmUmmTJk_k8yiPr1TWnAhuPr44NwL9wBwi9ETpkKMEUJUIoIoJYRzxpE6A0OsGI0op-gcDA9A1BPxAFx5v-tfrii_BAPMBI8xi4fgfaprE22029oA53VwTbuH66IuquJbh6Kp4cN0M18_wknbloU1MDRwsW-t863NgtMl_NCVruGy0lsLn3XQ1-Ai16W3N6c7Ap8v881sEa3eXpezySrKGOIhwrHIcmmlZFhqIo2QxKQsp9hSYqxQxuTM5iIlRCIVK8UUFZQIo9NUccYEHYH7Y2_rmq_O-pBUhc9sWeraNp1PJGaUx4r3IDmCmWu8dzZPWldU2u0TjJKDyOSvyD50d2rv0sqa38jJXA-Mj4Dvhye7pnN1v_a_yh_cK3kH</recordid><startdate>200311</startdate><enddate>200311</enddate><creator>Widjaja, Effendi</creator><creator>Crane, Nicole</creator><creator>Chen, Tso-Ching</creator><creator>Morris, Michael D.</creator><creator>Ignelzi, Michael A.</creator><creator>McCreadie, Barbara R.</creator><general>SAGE Publications</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>200311</creationdate><title>Band-Target Entropy Minimization (BTEM) Applied to Hyperspectral Raman Image Data</title><author>Widjaja, Effendi ; Crane, Nicole ; Chen, Tso-Ching ; Morris, Michael D. ; Ignelzi, Michael A. ; McCreadie, Barbara R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c405t-186cf7e77417a27d672db4f31e32de69ddf4ef6b227098994936326dabb954463</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2003</creationdate><topic>Aged</topic><topic>Algorithms</topic><topic>Animals</topic><topic>Computer Simulation</topic><topic>Entropy</topic><topic>Femur - chemistry</topic><topic>Femur - pathology</topic><topic>Humans</topic><topic>Image Interpretation, Computer-Assisted - methods</topic><topic>Male</topic><topic>Mice</topic><topic>Reproducibility of Results</topic><topic>Sensitivity and Specificity</topic><topic>Signal Processing, Computer-Assisted</topic><topic>Skull - chemistry</topic><topic>Skull - embryology</topic><topic>Skull - pathology</topic><topic>Spectrum Analysis, Raman - methods</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Widjaja, Effendi</creatorcontrib><creatorcontrib>Crane, Nicole</creatorcontrib><creatorcontrib>Chen, Tso-Ching</creatorcontrib><creatorcontrib>Morris, Michael D.</creatorcontrib><creatorcontrib>Ignelzi, Michael A.</creatorcontrib><creatorcontrib>McCreadie, Barbara R.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Applied spectroscopy</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Widjaja, Effendi</au><au>Crane, Nicole</au><au>Chen, Tso-Ching</au><au>Morris, Michael D.</au><au>Ignelzi, Michael A.</au><au>McCreadie, Barbara R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Band-Target Entropy Minimization (BTEM) Applied to Hyperspectral Raman Image Data</atitle><jtitle>Applied spectroscopy</jtitle><addtitle>Appl Spectrosc</addtitle><date>2003-11</date><risdate>2003</risdate><volume>57</volume><issue>11</issue><spage>1353</spage><epage>1362</epage><pages>1353-1362</pages><issn>0003-7028</issn><eissn>1943-3530</eissn><abstract>Band-target entropy minimization (BTEM) has been applied to extraction of component spectra from hyperspectral Raman images. In this method singular value decomposition is used to calculate the eigenvectors of the spectroscopic image data set. Bands in non-noise eigenvectors that would normally be used for recovery of spectra are examined for localized spectral features. For a targeted (identified) band, information entropy minimization or a closely related algorithm is used to recover the spectrum containing this feature from the non-noise eigenvectors, plus the next 5–30 eigenvectors, in which noise predominates. Tests for which eigenvectors to include are described. The method is demonstrated on one synthesized Raman image data set and two bone tissue specimens. By inclusion of small amounts of signal that would be unused in other methods, BTEM enables the extraction of a larger number of component spectra than are otherwise obtainable. An improvement in signal/noise ratio of the recovered spectra is also obtained.</abstract><cop>London, England</cop><pub>SAGE Publications</pub><pmid>14658148</pmid><doi>10.1366/000370203322554509</doi><tpages>10</tpages></addata></record> |
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| subjects | Aged Algorithms Animals Computer Simulation Entropy Femur - chemistry Femur - pathology Humans Image Interpretation, Computer-Assisted - methods Male Mice Reproducibility of Results Sensitivity and Specificity Signal Processing, Computer-Assisted Skull - chemistry Skull - embryology Skull - pathology Spectrum Analysis, Raman - methods |
| title | Band-Target Entropy Minimization (BTEM) Applied to Hyperspectral Raman Image Data |
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