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Direct reconstruction of tissue parameters from differential multifrequency EITin vivo
- Source :
- Physiological Measurement. 27:S93-S101
- Publication Year :
- 2006
- Publisher :
- IOP Publishing, 2006.
-
Abstract
- The basic purpose of electrical impedance tomography (EIT) is the reconstruction of conductivity distributions. While multifrequency measurements are of common use, the majority of reconstructed images are still conductivity distributions from one single frequency. More interesting than conductivities at each frequency are electrical tissue parameters, which describe the frequency-dependent conductivity changes of tissue. These parameters give information about physiological or electrical properties of tissues. By using this spectral information, a classification of different tissue types is possible. To get a distribution of tissue parameters, usually a posterior fitting of a tissue model to the conductivity spectra obtained with classical reconstruction algorithms at various frequencies is used. In this work, a single-step reconstruction algorithm for differential imaging was developed for the direct estimation of Cole parameters. This method is termed differential parametric reconstruction. The Cole model was used as the underlying tissue model, where only the relative changes of the two conductivity parameters sigma(0) and sigma(infinity) were reconstructed and the other two parameters of the model which are less identifiable were set to constant values. The reconstruction algorithm was tested with simulated noisy datasets and real measurement data from EIT measurements on the human thorax. These measurements were taken from healthy subjects and from patients with a serious lung injury. The new method yields a good image quality and higher robustness against noise compared to conventional reconstruction methods.
- Subjects :
- Physiology
Quantitative Biology::Tissues and Organs
Physics::Medical Physics
Biomedical Engineering
Biophysics
Pulmonary Edema
Lung injury
Models, Biological
Sensitivity and Specificity
Noise (electronics)
Quality (physics)
Robustness (computer science)
Physiology (medical)
Image Interpretation, Computer-Assisted
Electric Impedance
Humans
Computer Simulation
Plethysmography, Impedance
Lung
Tomography
Electrical impedance tomography
Parametric statistics
Physics
Phantoms, Imaging
Reproducibility of Results
Reconstruction algorithm
Image Enhancement
Distribution (mathematics)
Algorithm
Algorithms
Biomedical engineering
Subjects
Details
- ISSN :
- 13616579 and 09673334
- Volume :
- 27
- Database :
- OpenAIRE
- Journal :
- Physiological Measurement
- Accession number :
- edsair.doi.dedup.....5b7a5bab4565e607066771ffae160069