Artificial neural networks based estimation of optical parameters by diffuse reflectance imaging under in vitro conditions

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dc.contributor.authorGokkan, Mahmut Ozan
dc.contributor.authorEngin, Mehmet
dc.date.accessioned2019-10-27T11:22:47Z
dc.date.available2019-10-27T11:22:47Z
dc.date.issued2017
dc.departmentEge Üniversitesien_US
dc.description.abstractOptical parameters (properties) of tissue-mimicking phantoms are determined through nonin-vasive optical imaging. Objective of this study is to decompose obtained diffuse reflectance into these optical properties such as absorption and scattering coefficients. To do so, transmission spectroscopy is firstly used to measure the coefficients via an experimental setup. Next, the optical properties of each characterized phantom are input for Monte Carlo (MC) simulations to get diffuse reflectance. Also, a surface image for each single phantom with its known optical properties is obliquely captured due to reflectance-based geometrical setup using CMOS camera that is positioned at 5 degrees angle to the phantoms. For the illumination of light, a laser light source at 633 nm wavelength is preferred, because optical properties of different components in a biological tissue on that wavelength are nonoverlapped. During in vitro measurements, we prepared 30 different mixture samples adding clinoleic intravenous lipid emulsion (CILE) and evans blue (EB) dye into a distilled water. Finally, all obtained diffuse reflectance values are used to estimate the optical coeffcients by artificial neural networks (ANNs) in inverse modeling. For a biological tissue it is found that the simulated and measured values in our results are in good agreement.en_US
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TUBITAK)Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [113E771]en_US
dc.description.sponsorshipThis work was supported by the Scientific and Technological Research Council of Turkey (TUBITAK), under Grant No. 113E771.en_US
dc.identifier.doi10.1142/S1793545816500279
dc.identifier.issn1793-5458
dc.identifier.issn1793-7205
dc.identifier.issn1793-5458en_US
dc.identifier.issn1793-7205en_US
dc.identifier.issue1en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://doi.org/10.1142/S1793545816500279
dc.identifier.urihttps://hdl.handle.net/11454/33082
dc.identifier.volume10en_US
dc.identifier.wosWOS:000393756600001en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherWorld Scientific Publ Co Pte Ltden_US
dc.relation.ispartofJournal of Innovative Optical Health Sciencesen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectOptical propertiesen_US
dc.subjectdiffuse reflectanceen_US
dc.subjectspectroscopyen_US
dc.subjectMonte Carlo simulationen_US
dc.subjectartificial neural networksen_US
dc.titleArtificial neural networks based estimation of optical parameters by diffuse reflectance imaging under in vitro conditionsen_US
dc.typeArticleen_US

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