Use of a priori information in estimating tissue resistivities-application to measured data

Date

1999-07-01

Author

Baysal, U
Eyüboğlu, Behçet Murat

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A statistically constrained minimum mean squares error estimator (MiMSEE) has been shown to be useful in estimating internal resistivity distribution by the use of simulated data. In this study, the performance of the MiMSEE algorithm is tested by using measured data from resistor phantoms. The MiMSEE uses a priori information on body geometry, electrode position, statistical properties of tissue resistivities, instrumentation noise and linearization error to calculate the optimum inverse matrix which maps the surface potentials to unknown regional resistivities. In this study, the MiMSEE is also constrained with the variance-covariance of the modelling error to improve the estimation accuracy. The data are obtained from two different phantom geometries, namely five-region and thorax. Using the measured data, the estimations are realized and errors are calculated. Then, the results are compared with the results obtained by using a conventional least squares error estimator (LSEE). The five-region model results show similarity with the simulation study results of Baysal and Eyuboglu. On the thorax model, the total estimation error is 34.2% with the MiMSEE compared with 856% with the LSEE. It is concluded that the MiMSEE is more robust than the LSEE and applicable to measured data.

Subject Keywords

Radiological and ultrasound technology, Radiology nuclear medicine and imaging

URI

https://hdl.handle.net/11511/39699

Journal

PHYSICS IN MEDICINE AND BIOLOGY

DOI

https://doi.org/10.1088/0031-9155/44/7/308

Collections

Department of Electrical and Electronics Engineering, Article

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Citation Formats

U. Baysal and B. M. Eyüboğlu, “Use of a priori information in estimating tissue resistivities-application to measured data,” PHYSICS IN MEDICINE AND BIOLOGY, pp. 1677–1689, 1999, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/39699.