Numerical Simulation of Tunable Terahertz Graphene-Based Sensor for Breast Tumor Detection
This article presents a modeling and analysis of a tunable graphene-based sensor for breast tumor detection operating in the terahertz frequency range using the wave concept iterative process (WCIP) method. Through the novel implementation approach of the biological tissues in the WCIP method, we ca...
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Veröffentlicht in: | IEEE sensors journal 2021-04, Vol.21 (8), p.9844-9851 |
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description | This article presents a modeling and analysis of a tunable graphene-based sensor for breast tumor detection operating in the terahertz frequency range using the wave concept iterative process (WCIP) method. Through the novel implementation approach of the biological tissues in the WCIP method, we can integrate the normal and tumor of human breast tissues into this algorithm. At the beginning, the details of the algorithms of human breast tissue and graphene modeling in the WCIP method are presented. In order to verify the results obtained by the WCIP algorithm, we presented a comparative study with the CST simulator. Then, using the WCIP method, the numerical simulation results demonstrate the capability of the proposed sensor to detect the normal breast tissue with good sensitivity of 7.11 (THz/RIU) and breast tumor with a high sensitivity of 8.21 THz/RIU and large figure of merits of 17.51 and 20.23 RIU −1 , respectively. Finally, the simplicity, efficiency and tunability are the benefits of the proposed sensor, which makes it suitable for breast tumor detection in the THz band. |
doi_str_mv | 10.1109/JSEN.2021.3060326 |
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Through the novel implementation approach of the biological tissues in the WCIP method, we can integrate the normal and tumor of human breast tissues into this algorithm. At the beginning, the details of the algorithms of human breast tissue and graphene modeling in the WCIP method are presented. In order to verify the results obtained by the WCIP algorithm, we presented a comparative study with the CST simulator. Then, using the WCIP method, the numerical simulation results demonstrate the capability of the proposed sensor to detect the normal breast tissue with good sensitivity of 7.11 (THz/RIU) and breast tumor with a high sensitivity of 8.21 THz/RIU and large figure of merits of 17.51 and 20.23 RIU −1 , respectively. Finally, the simplicity, efficiency and tunability are the benefits of the proposed sensor, which makes it suitable for breast tumor detection in the THz band.</description><identifier>ISSN: 1530-437X</identifier><identifier>EISSN: 1558-1748</identifier><identifier>DOI: 10.1109/JSEN.2021.3060326</identifier><identifier>CODEN: ISJEAZ</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Algorithms ; Biological system modeling ; Biology ; Breast ; breast cancer ; Breast tissue ; Breast tumors ; Comparative studies ; Computer simulation ; Frequency ranges ; Graphene ; Iterative methods ; Mathematical model ; Mathematical models ; Sensitivity ; Sensor ; Sensors ; terahertz band ; Terahertz frequencies ; Tissues ; Tumors ; wave concept iterative process (WCIP) method</subject><ispartof>IEEE sensors journal, 2021-04, Vol.21 (8), p.9844-9851</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c293t-85deb924c29c2cfe4fe37413a6cca51f56822ae7cc4694dfa9ed6a425cc2cc7b3</citedby><cites>FETCH-LOGICAL-c293t-85deb924c29c2cfe4fe37413a6cca51f56822ae7cc4694dfa9ed6a425cc2cc7b3</cites><orcidid>0000-0002-7248-6121</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9357347$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,777,781,793,27905,27906,54739</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9357347$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Hlali, Aymen</creatorcontrib><creatorcontrib>Oueslati, Afef</creatorcontrib><creatorcontrib>Zairi, Hassen</creatorcontrib><title>Numerical Simulation of Tunable Terahertz Graphene-Based Sensor for Breast Tumor Detection</title><title>IEEE sensors journal</title><addtitle>JSEN</addtitle><description>This article presents a modeling and analysis of a tunable graphene-based sensor for breast tumor detection operating in the terahertz frequency range using the wave concept iterative process (WCIP) method. Through the novel implementation approach of the biological tissues in the WCIP method, we can integrate the normal and tumor of human breast tissues into this algorithm. At the beginning, the details of the algorithms of human breast tissue and graphene modeling in the WCIP method are presented. In order to verify the results obtained by the WCIP algorithm, we presented a comparative study with the CST simulator. Then, using the WCIP method, the numerical simulation results demonstrate the capability of the proposed sensor to detect the normal breast tissue with good sensitivity of 7.11 (THz/RIU) and breast tumor with a high sensitivity of 8.21 THz/RIU and large figure of merits of 17.51 and 20.23 RIU −1 , respectively. Finally, the simplicity, efficiency and tunability are the benefits of the proposed sensor, which makes it suitable for breast tumor detection in the THz band.</description><subject>Algorithms</subject><subject>Biological system modeling</subject><subject>Biology</subject><subject>Breast</subject><subject>breast cancer</subject><subject>Breast tissue</subject><subject>Breast tumors</subject><subject>Comparative studies</subject><subject>Computer simulation</subject><subject>Frequency ranges</subject><subject>Graphene</subject><subject>Iterative methods</subject><subject>Mathematical model</subject><subject>Mathematical models</subject><subject>Sensitivity</subject><subject>Sensor</subject><subject>Sensors</subject><subject>terahertz band</subject><subject>Terahertz frequencies</subject><subject>Tissues</subject><subject>Tumors</subject><subject>wave concept iterative process (WCIP) method</subject><issn>1530-437X</issn><issn>1558-1748</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kEtLAzEUhYMoWKs_QNwMuJ6a52SytLVWpdRFK4ibkGZu6JR51GRmob_eDC0uLvceOOdc-BC6JXhCCFYPb-v5akIxJROGM8xodoZGRIg8JZLn58PNcMqZ_LxEVyHsMSZKCjlCX6u-Bl9aUyXrsu4r05Vtk7Qu2fSN2VaQbMCbHfjuN1l4c9hBA-nUBCiSNTSh9YmLM_VgQhcjdRRP0IEdWq7RhTNVgJvTHqOP5_lm9pIu3xevs8dlaqliXZqLAraK8qgstQ64AyY5YSaz1gjiRJZTakBayzPFC2cUFJnhVNhot3LLxuj-2Hvw7XcPodP7tvdNfKmpwExgQoSKLnJ0Wd-G4MHpgy9r4380wXpAqAeEekCoTwhj5u6YKQHg36-YkIxL9gfSO247</recordid><startdate>20210415</startdate><enddate>20210415</enddate><creator>Hlali, Aymen</creator><creator>Oueslati, Afef</creator><creator>Zairi, Hassen</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7U5</scope><scope>8FD</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0002-7248-6121</orcidid></search><sort><creationdate>20210415</creationdate><title>Numerical Simulation of Tunable Terahertz Graphene-Based Sensor for Breast Tumor Detection</title><author>Hlali, Aymen ; Oueslati, Afef ; Zairi, Hassen</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c293t-85deb924c29c2cfe4fe37413a6cca51f56822ae7cc4694dfa9ed6a425cc2cc7b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Algorithms</topic><topic>Biological system modeling</topic><topic>Biology</topic><topic>Breast</topic><topic>breast cancer</topic><topic>Breast tissue</topic><topic>Breast tumors</topic><topic>Comparative studies</topic><topic>Computer simulation</topic><topic>Frequency ranges</topic><topic>Graphene</topic><topic>Iterative methods</topic><topic>Mathematical model</topic><topic>Mathematical models</topic><topic>Sensitivity</topic><topic>Sensor</topic><topic>Sensors</topic><topic>terahertz band</topic><topic>Terahertz frequencies</topic><topic>Tissues</topic><topic>Tumors</topic><topic>wave concept iterative process (WCIP) method</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hlali, Aymen</creatorcontrib><creatorcontrib>Oueslati, Afef</creatorcontrib><creatorcontrib>Zairi, Hassen</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>IEEE sensors journal</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Hlali, Aymen</au><au>Oueslati, Afef</au><au>Zairi, Hassen</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Numerical Simulation of Tunable Terahertz Graphene-Based Sensor for Breast Tumor Detection</atitle><jtitle>IEEE sensors journal</jtitle><stitle>JSEN</stitle><date>2021-04-15</date><risdate>2021</risdate><volume>21</volume><issue>8</issue><spage>9844</spage><epage>9851</epage><pages>9844-9851</pages><issn>1530-437X</issn><eissn>1558-1748</eissn><coden>ISJEAZ</coden><abstract>This article presents a modeling and analysis of a tunable graphene-based sensor for breast tumor detection operating in the terahertz frequency range using the wave concept iterative process (WCIP) method. Through the novel implementation approach of the biological tissues in the WCIP method, we can integrate the normal and tumor of human breast tissues into this algorithm. At the beginning, the details of the algorithms of human breast tissue and graphene modeling in the WCIP method are presented. In order to verify the results obtained by the WCIP algorithm, we presented a comparative study with the CST simulator. Then, using the WCIP method, the numerical simulation results demonstrate the capability of the proposed sensor to detect the normal breast tissue with good sensitivity of 7.11 (THz/RIU) and breast tumor with a high sensitivity of 8.21 THz/RIU and large figure of merits of 17.51 and 20.23 RIU −1 , respectively. Finally, the simplicity, efficiency and tunability are the benefits of the proposed sensor, which makes it suitable for breast tumor detection in the THz band.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/JSEN.2021.3060326</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0002-7248-6121</orcidid></addata></record> |
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subjects | Algorithms Biological system modeling Biology Breast breast cancer Breast tissue Breast tumors Comparative studies Computer simulation Frequency ranges Graphene Iterative methods Mathematical model Mathematical models Sensitivity Sensor Sensors terahertz band Terahertz frequencies Tissues Tumors wave concept iterative process (WCIP) method |
title | Numerical Simulation of Tunable Terahertz Graphene-Based Sensor for Breast Tumor Detection |
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