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In vivo estimation of head tissue conductivities using bound constrained optimization

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dc.contributor.author Ouypornkochagorn T.
dc.contributor.author Ouypornkochagorn S.
dc.date.accessioned 2021-04-05T03:02:59Z
dc.date.available 2021-04-05T03:02:59Z
dc.date.issued 2019
dc.identifier.issn 906964
dc.identifier.other 2-s2.0-85064503315
dc.identifier.uri https://ir.swu.ac.th/jspui/handle/123456789/12364
dc.identifier.uri https://www.scopus.com/inward/record.uri?eid=2-s2.0-85064503315&doi=10.1007%2fs10439-019-02254-9&partnerID=40&md5=9dd231176d8a4eb2bd492b00d679ff44
dc.description.abstract The 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.subject Cerebrospinal fluid
dc.subject Electric impedance
dc.subject Electric impedance measurement
dc.subject Electric impedance tomography
dc.subject Number theory
dc.subject Tissue
dc.subject Bio-impedance
dc.subject Bound constrained optimization
dc.subject Cerebro spinal fluids
dc.subject Electrical impe dance tomography (EIT)
dc.subject Electrical impedance tomography
dc.subject Initial guess
dc.subject Tissue conductivity
dc.subject Unconstrained optimization
dc.subject Constrained optimization
dc.subject article
dc.subject cerebrospinal fluid
dc.subject computer assisted impedance tomography
dc.subject conductance
dc.subject gray matter
dc.subject human tissue
dc.subject in vivo study
dc.subject scalp
dc.subject simulation
dc.subject skull
dc.subject white matter
dc.subject adult
dc.subject biological model
dc.subject computer simulation
dc.subject human
dc.subject impedance
dc.subject Adult
dc.subject Cerebrospinal Fluid
dc.subject Computer Simulation
dc.subject Electric Impedance
dc.subject Gray Matter
dc.subject Humans
dc.subject Models, Biological
dc.subject Scalp
dc.subject Skull
dc.subject White Matter
dc.title In vivo estimation of head tissue conductivities using bound constrained optimization
dc.type Article
dc.rights.holder Scopus
dc.identifier.bibliograpycitation Annals of Biomedical Engineering. Vol 47, No.7 (2019), p.1575-1583
dc.identifier.doi 10.1007/s10439-019-02254-9


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