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

2
0

Issued Date

2019

Resource Type

Article

File Type

application/pdf

ISSN

906964

DOI

10.1007/s10439-019-02254-9

Other identifier(s)

2-s2.0-85064503315

Rights Holder(s)

มหาวิทยาลัยศรีนครินทรวิโรฒ

Bibliographic Citation

Annals of Biomedical Engineering. Vol 47, No.7 (2019), p.1575-1583

Suggested Citation

Ouypornkochagorn T., Ouypornkochagorn S. In vivo estimation of head tissue conductivities using bound constrained optimization. Annals of Biomedical Engineering. Vol 47, No.7 (2019), p.1575-1583. doi:10.1007/s10439-019-02254-9 Retrieved from: https://hdl.handle.net/20.500.14740/5259

Title

In vivo estimation of head tissue conductivities using bound constrained optimization

Author(s)

Ouypornkochagorn T.
 Ouypornkochagorn S.

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.

Subject(s)

Cerebrospinal fluid
 Electric impedance
 Electric impedance measurement
 Electric impedance tomography
 Number theory
 Tissue
 Bio-impedance
 Bound constrained optimization
 Cerebro spinal fluids
 Electrical impe dance tomography (EIT)
 Electrical impedance tomography
 Initial guess
 Tissue conductivity
 Unconstrained optimization
 Constrained optimization
 Article
 Cerebrospinal fluid
 Computer assisted impedance tomography
 Conductance
 Gray matter
 Human tissue
 In vivo study
 Scalp
 Simulation
 Skull
 White matter
 Adult
 Biological model
 Computer simulation
 Human
 Impedance
 Adult
 Cerebrospinal Fluid
 Computer Simulation
 Electric Impedance
 Gray Matter
 Humans
 Models, Biological
 Scalp
 Skull
 White Matter

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URI

https://hdl.handle.net/20.500.14740/5259

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Scopus: Year 1983-2021

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