Use of a priori information in estimating tissue resistivities - a simulation study

Accurate estimation of tissue resistivities in vivo is needed to construct reliable human body volume conductor models in solving forward and inverse bioelectric field problems. The necessary data for the estimation can be obtained by using ht four-electrode impedance measurement technique, usually employed in electrical impedance tomography. In this study, a priori geometrical information with statistical properties of regional resistivities and linearization error as well as instrumentation noise has been incorporated into a new resistivity estimation algorithm which is called a statistically constrained minimum mean squares error estimator (MiMSEE) to improve estimation accuracy. MiMSEE intakes geometrical information from the image which is obtained by using a high-resolution imaging modality. This study is an extension of earlier work by Eyuboglu et al and obtains simulated measurements from two numerical models containing five and six regions on a background region. Also, estimations are repeated by suing up to eight multiple current electrode pairs, in order to observe the effect of estimation performance while increasing the number of measurements up to 96. The results are compared with a conventional least squares error estimator (LSEE) which is used in one-pass algorithms. It is shown that the MiMSEE estimation error is up to 27 times smaller than the LSEE error which is realized for a small, high-contrast region, for example the aorta. In estimating the regional resistivities, the MiMSEE algorithm requires 25.8 (for the five-region resistivity distribution) and 22.2 (for the six-region resistivity distribution) times more computational time than the LSEE. This gap between the computational times of the two algorithms decreases are the number of regions increases.


Eyüboğlu, Behçet Murat; WOLF, PD (IOP Publishing, 1994-01-01)
In order to measure in vivo resistivity of tissues in the thorax, the possibility of combining anatomical data extracted from high-resolution images with multiple-electrode impedance measurements, a priori knowledge of the range of tissue resistivities, and a priori data on the instrumentation noise is assessed in this study. A statistically constrained minimum-mean-square error estimator (MIMSEE) that minimizes the effects of linearization errors and instrumentation noise is developed and compared to the c...
Experimental results for 2D magnetic resonance electrical impedance tomography (MR-EIT) using magnetic flux density in one direction
Birgul, O; Eyüboğlu, Behçet Murat; Ider, YZ (IOP Publishing, 2003-11-07)
Magnetic resonance electrical impedance tomography (MR-EIT) is an emerging imaging technique that reconstructs conductivity images using magnetic flux density measurements acquired employing MRI together with conventional EIT measurements. In this study, experimental MR-EIT images from phantoms with conducting and insulator objects are presented. The technique is implemented using the 0.15 T Middle East Technical University MRI system. The dc current method used in magnetic resonance current density imaging...
Sensitivity of EEG and MEG measurements to tissue conductivity
Gençer, Nevzat Güneri (IOP Publishing, 2004-03-07)
Monitoring the electrical activity inside the human brain using electrical and magnetic field measurements requires a mathematical head model. Using this model the potential distribution in the head and magnetic fields outside the head are computed for a given source distribution. This is called the forward problem of the electro-magnetic source imaging. Accurate representation of the source distribution requires a realistic geometry and an accurate conductivity model. Deviation from the actual head is one ...
Lorentz force electrical impedance tomography using magnetic field measurements
ZENGİN, Reyhan; Gençer, Nevzat Güneri (IOP Publishing, 2016-08-21)
In this study, magnetic field measurement technique is investigated to image the electrical conductivity properties of biological tissues using Lorentz forces. This technique is based on electrical current induction using ultrasound together with an applied static magnetic field. The magnetic field intensity generated due to induced currents is measured using two coil configurations, namely, a rectangular loop coil and a novel xy coil pair. A time-varying voltage is picked-up and recorded while the acoustic...
Distinguishability for magnetic resonance-electrical impedance tomography (MR-EIT)
Altunel, Haluk; Eyüboğlu, Behçet Murat; Koksal, Adnan (IOP Publishing, 2007-01-21)
A distinguishability measure is defined for magnetic resonance-electrical impedance tomography (MR-EIT) based on magnetic flux density measurements. This general definition is valid for 2D and 3D structures of any shape. As a specific case, a 2D cylindrical body with concentric inhomogeneity is considered and a bound of the distinguishability is analytically formulated. Distinguishabilities obtained with potential and magnetic flux density measurements are compared.
Citation Formats
U. Baysal and B. M. Eyüboğlu, “Use of a priori information in estimating tissue resistivities - a simulation study,” PHYSICS IN MEDICINE AND BIOLOGY, pp. 3589–3606, 1998, Accessed: 00, 2020. [Online]. Available: