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dc.contributor.authorOuypornkochagorn T.
dc.contributor.authorOuypornkochagorn S.
dc.date.accessioned2021-04-05T03:02:59Z-
dc.date.available2021-04-05T03:02:59Z-
dc.date.issued2019
dc.identifier.issn906964
dc.identifier.other2-s2.0-85064503315
dc.identifier.urihttps://ir.swu.ac.th/jspui/handle/123456789/12364-
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85064503315&doi=10.1007%2fs10439-019-02254-9&partnerID=40&md5=9dd231176d8a4eb2bd492b00d679ff44
dc.description.abstractThe conductivity of head tissues was noninva-sively estimated using electrical impedance tomography technique. Instead of using conventional unconstrained optimization method to estimate the conductivities, a constrained method with the scaled-logistic function was employed to improve the very high sensitivity of the skull region resulting in accuracy and robustness improvement. Estimation of five conductivities i.e. scalp, skull, cerebrospinal fluid (CSF), grey matter (GM), and white matter (WM) conductivity was investigated by simulation on random and low-value initial guesses. Simulation results showed that the performance of the unconstrained method depended directly to the difference between the exact skull conductivity value and the initial guess value of the skull conductivity. However, the approached constrained method was independent of the guess selection. It can reduce the sensitivity of the skull region by 126 times and reduce the condition number of the sensitivity matrix by 13–17 times. The estimation resulted in only positive and in-range of reported conductivity values. The estimation error of the skull conductivity decreased by 15% and the robustness increased by 2 times. However, the estimation of the CSF, the WM, and the GM may be not reliable due to the very low sensitivity of these regions in both methods. © Springer. All rights reserved.
dc.subjectCerebrospinal fluid
dc.subjectElectric impedance
dc.subjectElectric impedance measurement
dc.subjectElectric impedance tomography
dc.subjectNumber theory
dc.subjectTissue
dc.subjectBio-impedance
dc.subjectBound constrained optimization
dc.subjectCerebro spinal fluids
dc.subjectElectrical impe dance tomography (EIT)
dc.subjectElectrical impedance tomography
dc.subjectInitial guess
dc.subjectTissue conductivity
dc.subjectUnconstrained optimization
dc.subjectConstrained optimization
dc.subjectarticle
dc.subjectcerebrospinal fluid
dc.subjectcomputer assisted impedance tomography
dc.subjectconductance
dc.subjectgray matter
dc.subjecthuman tissue
dc.subjectin vivo study
dc.subjectscalp
dc.subjectsimulation
dc.subjectskull
dc.subjectwhite matter
dc.subjectadult
dc.subjectbiological model
dc.subjectcomputer simulation
dc.subjecthuman
dc.subjectimpedance
dc.subjectAdult
dc.subjectCerebrospinal Fluid
dc.subjectComputer Simulation
dc.subjectElectric Impedance
dc.subjectGray Matter
dc.subjectHumans
dc.subjectModels, Biological
dc.subjectScalp
dc.subjectSkull
dc.subjectWhite Matter
dc.titleIn vivo estimation of head tissue conductivities using bound constrained optimization
dc.typeArticle
dc.rights.holderScopus
dc.identifier.bibliograpycitationAnnals of Biomedical Engineering. Vol 47, No.7 (2019), p.1575-1583
dc.identifier.doi10.1007/s10439-019-02254-9
Appears in Collections:Scopus 1983-2021

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