{"title":"利用近红外照明的悄悄话廊模式硅基谐振器组织成像技术","authors":"Suren Gigoyan;Naimeh Ghafarian;Aidin Taeb;Mohammad-Reza Nezhad-Ahmadi;Slim Boumaiza","doi":"10.1109/LMWT.2024.3436619","DOIUrl":null,"url":null,"abstract":"This letter introduces a novel technique for achieving high-precision 2-D tissue imaging by exploiting the sensitivity of a whispering gallery mode (WGM) silicon resonator’s conductivity to near-infrared (NIR) illumination. The WGM silicon resonator, in conjunction with a microstrip line, acts as the primary sensing element. To ensure precise imaging, the tissue under test (TUT) specimen is meticulously positioned on the resonator at a specific distance and manipulated using a 2-D scanner with 3-mm steps. By directing NIR light emitted from a light-emitting diode (LED) through the scanning TUT sample onto the WGM resonator, variations in the silicon resonator’s conductivity are harnessed, resulting in changes in the magnitude of the transmission coefficient (\n<inline-formula> <tex-math>$S_{21}$ </tex-math></inline-formula>\n). The alteration in \n<inline-formula> <tex-math>$S_{21}$ </tex-math></inline-formula>\n during scanning is contingent upon the absorption of NIR through TUT. As the TUT undergoes scanning, the measured transmission coefficient \n<inline-formula> <tex-math>$S_{21}$ </tex-math></inline-formula>\n parameters are transformed into a 2-D image map. This method effectively discriminates between fat and muscle tissues, underscoring the feasibility and practicality of this approach. Importantly, the proposed methodology shows promise for detecting various biosensors and holds potential applications in breast cancer detection.","PeriodicalId":73297,"journal":{"name":"IEEE microwave and wireless technology letters","volume":"34 10","pages":"1210-1213"},"PeriodicalIF":0.0000,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Tissue Imaging Technique Using Near-Infrared Illumination of Whispering Gallery Mode Silicon-Based Resonator\",\"authors\":\"Suren Gigoyan;Naimeh Ghafarian;Aidin Taeb;Mohammad-Reza Nezhad-Ahmadi;Slim Boumaiza\",\"doi\":\"10.1109/LMWT.2024.3436619\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This letter introduces a novel technique for achieving high-precision 2-D tissue imaging by exploiting the sensitivity of a whispering gallery mode (WGM) silicon resonator’s conductivity to near-infrared (NIR) illumination. The WGM silicon resonator, in conjunction with a microstrip line, acts as the primary sensing element. To ensure precise imaging, the tissue under test (TUT) specimen is meticulously positioned on the resonator at a specific distance and manipulated using a 2-D scanner with 3-mm steps. By directing NIR light emitted from a light-emitting diode (LED) through the scanning TUT sample onto the WGM resonator, variations in the silicon resonator’s conductivity are harnessed, resulting in changes in the magnitude of the transmission coefficient (\\n<inline-formula> <tex-math>$S_{21}$ </tex-math></inline-formula>\\n). The alteration in \\n<inline-formula> <tex-math>$S_{21}$ </tex-math></inline-formula>\\n during scanning is contingent upon the absorption of NIR through TUT. As the TUT undergoes scanning, the measured transmission coefficient \\n<inline-formula> <tex-math>$S_{21}$ </tex-math></inline-formula>\\n parameters are transformed into a 2-D image map. This method effectively discriminates between fat and muscle tissues, underscoring the feasibility and practicality of this approach. Importantly, the proposed methodology shows promise for detecting various biosensors and holds potential applications in breast cancer detection.\",\"PeriodicalId\":73297,\"journal\":{\"name\":\"IEEE microwave and wireless technology letters\",\"volume\":\"34 10\",\"pages\":\"1210-1213\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-08-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE microwave and wireless technology letters\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10638548/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"0\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE microwave and wireless technology letters","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10638548/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Tissue Imaging Technique Using Near-Infrared Illumination of Whispering Gallery Mode Silicon-Based Resonator
This letter introduces a novel technique for achieving high-precision 2-D tissue imaging by exploiting the sensitivity of a whispering gallery mode (WGM) silicon resonator’s conductivity to near-infrared (NIR) illumination. The WGM silicon resonator, in conjunction with a microstrip line, acts as the primary sensing element. To ensure precise imaging, the tissue under test (TUT) specimen is meticulously positioned on the resonator at a specific distance and manipulated using a 2-D scanner with 3-mm steps. By directing NIR light emitted from a light-emitting diode (LED) through the scanning TUT sample onto the WGM resonator, variations in the silicon resonator’s conductivity are harnessed, resulting in changes in the magnitude of the transmission coefficient (
$S_{21}$
). The alteration in
$S_{21}$
during scanning is contingent upon the absorption of NIR through TUT. As the TUT undergoes scanning, the measured transmission coefficient
$S_{21}$
parameters are transformed into a 2-D image map. This method effectively discriminates between fat and muscle tissues, underscoring the feasibility and practicality of this approach. Importantly, the proposed methodology shows promise for detecting various biosensors and holds potential applications in breast cancer detection.