Utilization of electrical impedance imaging for estimation of in-vivo tissue resistivities

B. Murat Eyuboglu; Theo C. Pilkington

doi:10.1117/12.151195

27 August 1993 Utilization of electrical impedance imaging for estimation of in-vivo tissue resistivities

B. Murat Eyuboglu, Theo C. Pilkington

Proceedings Volume 1887, Physiological Imaging, Spectroscopy, and Early-Detection Diagnostic Methods; (1993) https://doi.org/10.1117/12.151195
Event: OE/LASE'93: Optics, Electro-Optics, and Laser Applications in Scienceand Engineering, 1993, Los Angeles, CA, United States

Abstract

In order to determine in vivo resistivity of tissues in the thorax, the possibility of combining electrical impedance imaging (EII) techniques with (1) anatomical data extracted from high resolution images, (2) a prior knowledge of tissue resistivities, and (3) a priori noise information was assessed in this study. A Least Square Error Estimator (LSEE) and a statistically constrained Minimum Mean Square Error Estimator (MiMSEE) were implemented to estimate regional electrical resistivities from potential measurements made on the body surface. A two dimensional boundary element model of the human thorax, which consists of four different conductivity regions (the skeletal muscle, the heart, the right lung, and the left lung) was adopted to simulate the measured EII torso potentials. The calculated potentials were then perturbed by simulated instrumentation noise. The signal information used to form the statistical constraint for the MiMSEE was obtained from a prior knowledge of the physiological range of tissue resistivities. The noise constraint was determined from a priori knowledge of errors due to linearization of the forward problem and to the instrumentation noise.

Citation Download Citation

B. Murat Eyuboglu and Theo C. Pilkington "Utilization of electrical impedance imaging for estimation of in-vivo tissue resistivities", Proc. SPIE 1887, Physiological Imaging, Spectroscopy, and Early-Detection Diagnostic Methods, (27 August 1993); https://doi.org/10.1117/12.151195

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KEYWORDS

Error analysis

Lung

Electrodes

Statistical analysis

Tissues

Heart

In vivo imaging

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