Publication:
In vivo estimation of head tissue conductivities using bound constrained optimization

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.date.issuedBE2562
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.format.mimetypeapplication/pdf
dc.identifier.citationAnnals of Biomedical Engineering. Vol 47, No.7 (2019), p.1575-1583
dc.identifier.doi10.1007/s10439-019-02254-9
dc.identifier.issn906964
dc.identifier.other2-s2.0-85064503315
dc.identifier.urihttps://hdl.handle.net/20.500.14740/5259
dc.rights.holderมหาวิทยาลัยศรีนครินทรวิโรฒ
dc.subject.otherCerebrospinal fluid
dc.subject.otherElectric impedance
dc.subject.otherElectric impedance measurement
dc.subject.otherElectric impedance tomography
dc.subject.otherNumber theory
dc.subject.otherTissue
dc.subject.otherBio-impedance
dc.subject.otherBound constrained optimization
dc.subject.otherCerebro spinal fluids
dc.subject.otherElectrical impe dance tomography (EIT)
dc.subject.otherElectrical impedance tomography
dc.subject.otherInitial guess
dc.subject.otherTissue conductivity
dc.subject.otherUnconstrained optimization
dc.subject.otherConstrained optimization
dc.subject.otherArticle
dc.subject.otherCerebrospinal fluid
dc.subject.otherComputer assisted impedance tomography
dc.subject.otherConductance
dc.subject.otherGray matter
dc.subject.otherHuman tissue
dc.subject.otherIn vivo study
dc.subject.otherScalp
dc.subject.otherSimulation
dc.subject.otherSkull
dc.subject.otherWhite matter
dc.subject.otherAdult
dc.subject.otherBiological model
dc.subject.otherComputer simulation
dc.subject.otherHuman
dc.subject.otherImpedance
dc.subject.otherAdult
dc.subject.otherCerebrospinal Fluid
dc.subject.otherComputer Simulation
dc.subject.otherElectric Impedance
dc.subject.otherGray Matter
dc.subject.otherHumans
dc.subject.otherModels, Biological
dc.subject.otherScalp
dc.subject.otherSkull
dc.subject.otherWhite Matter
dc.titleIn vivo estimation of head tissue conductivities using bound constrained optimization
dc.typeArticle
dspace.entity.typePublication
swu.datasource.scopushttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85064503315&doi=10.1007%2fs10439-019-02254-9&partnerID=40&md5=9dd231176d8a4eb2bd492b00d679ff44

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