Tissue resistivity estimation in the presence of positional and geometrical uncertainties

Date

2000-08-01

Author

Baysal, U
Eyüboğlu, Behçet Murat

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Geometrical uncertainties (organ boundary variation and electrode position uncertainties) are the biggest sources of error in estimating electrical resistivity of tissues from body surface measurements. In this study, in order to decrease estimation errors, the statistically constrained minimum mean squared error estimation algorithm (MiMSEE) is constrained with a priori knowledge of the geometrical uncertainties in addition to the constraints based on geometry, resistivity range, linearization and instrumentation errors. The MiMSEE calculates an optimum inverse matrix, which maps the surface measurements to the unknown resistivity distribution. The required data are obtained from four-electrode impedance measurements, similar to injected-current electrical impedance tomography (EIT). In this study, the surface measurements are simulated by using a numerical thorax model. The data are perturbed with additive instrumentation noise. Simulated surface measurements are then used to estimate the tissue resistivities by using the proposed algorithm. The results are compared with the results of conventional least squares error estimator (LSEE). Depending on the region, the MiMSEE yields an estimation error between 0.42% and 31.3% compared with 7.12% to 2010% for the LSEE. It is shown that the MiMSEE is quite robust even in the case of geometrical uncertainties.

Subject Keywords

Tomography

URI

https://hdl.handle.net/11511/32791

Journal

PHYSICS IN MEDICINE AND BIOLOGY

DOI

https://doi.org/10.1088/0031-9155/45/8/322

Collections

Department of Electrical and Electronics Engineering, Article

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Citation Formats

U. Baysal and B. M. Eyüboğlu, “Tissue resistivity estimation in the presence of positional and geometrical uncertainties,” PHYSICS IN MEDICINE AND BIOLOGY, pp. 2373–2388, 2000, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/32791.