Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
ESTIMATION OF TISSUE RESISTIVITIES FROM MULTIPLE-ELECTRODE IMPEDANCE MEASUREMENTS
Date
1994-01-01
Author
Eyüboğlu, Behçet Murat
WOLF, PD
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
235
views
0
downloads
Cite This
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 conventional least-squares error estimator (LSEE). The MIMSEE requires a priori signal and noise information. The statistical constraint signal information was obtained from a priori knowledge of the physiologically allowed range of regional resistivities. The noise constraint information was obtained from a priori knowledge of the linearization error and the instrumentation noise. The torso potentials were simulated by employing a three-dimensional canine torso model. The model consists of four different conductivity regions: heart, right lung, left lung, and body. It is demonstrated that the statistically constrained MIMSEE performs significantly better than the LSEE in determining resistivities, The results based on the torso model indicate that regional resistivities can be estimated to within 40% accuracy of their true values by utilizing a statistically constrained MIMSEE, even if the instrumentation noise is comparable to the measured torso potentials. The errors obtained using the LSEE with the same linearized transfer function and level of instrumentation noise were about five times larger than those obtained using the MIMSEE. For larger measurement errors the MIMSEE performs even better when compared to the LSEE.
Subject Keywords
Radiological and Ultrasound Technology
,
Radiology Nuclear Medicine and imaging
URI
https://hdl.handle.net/11511/44803
Journal
PHYSICS IN MEDICINE AND BIOLOGY
DOI
https://doi.org/10.1088/0031-9155/39/1/001
Collections
Department of Electrical and Electronics Engineering, Article
Suggestions
OpenMETU
Core
Use of a priori information in estimating tissue resistivities - a simulation study
Baysal, U; Eyüboğlu, Behçet Murat (IOP Publishing, 1998-12-01)
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...
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...
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...
Current constrained voltage scaled reconstruction (CCVSR) algorithm for MR-EIT and its performance with different probing current patterns
Birgul, O; Eyüboğlu, Behçet Murat; Ider, YZ (IOP Publishing, 2003-03-07)
Conventional injected-current electrical impedance tomography (EIT) and magnetic resonance imaging (MRI) techniques can be combined to reconstruct high resolution true conductivity images. The magnetic flux density distribution generated by the internal current density distribution is extracted from MR phase images. This information is used to form a fine detailed conductivity image using an Ohm's law based update equation. The reconstructed conductivity image is assumed to differ from the true image by a s...
Forward problem solution of electromagnetic source imaging using a new BEM formulation with high-order elements
Gençer, Nevzat Güneri (IOP Publishing, 1999-09-01)
Representations of the active cell populations on the cortical surface via electric and magnetic measurements are known as electromagnetic source images (EMSIs) of the human brain. Numerical solution of the potential and magnetic fields for a given electrical source distribution in the human brain is an essential part of electromagnetic source imaging. In this study, the performance of the boundary element method (BEM) is explored with different surface element types. A new BEM formulation is derived that m...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
B. M. Eyüboğlu and P. WOLF, “ESTIMATION OF TISSUE RESISTIVITIES FROM MULTIPLE-ELECTRODE IMPEDANCE MEASUREMENTS,”
PHYSICS IN MEDICINE AND BIOLOGY
, pp. 1–17, 1994, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/44803.