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Accounting for hardware imperfections in EIT image reconstruction algorithms.

Alzbeta E Hartinger¹, Hervé Gagnon, Robert Guardo

¹Institut de génie biomédical, Ecole Polytechnique de Montréal, Montréal H3T 1J4, Canada.

Physiological Measurement

|August 1, 2007

Summary

Electrical impedance tomography (EIT) image artifacts can be reduced by integrating hardware imperfection models into reconstruction algorithms. This improves image quality, particularly for frequency difference EIT.

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Area of Science:

Biomedical Engineering
Medical Imaging
Electrical Engineering

Background:

Electrical impedance tomography (EIT) is a non-invasive imaging technique.
EIT reconstructs conductivity distributions, producing absolute, time difference, and frequency difference images.
Reconstruction algorithms are susceptible to errors from inaccurate modeling and measurements, leading to image artifacts.

Purpose of the Study:

To propose and evaluate a method for eliminating EIT image artifacts.
The method integrates a model of system hardware imperfections into reconstruction algorithms.
To assess the effectiveness of the proposed method on absolute, time difference, and frequency difference EIT images.

Main Methods:

Developed a method to incorporate hardware imperfection models into EIT reconstruction algorithms.
Acquired data on a resistor mesh phantom.
Reconstructed absolute, time difference, and frequency difference EIT images with and without the hardware model.

Main Results:

Images reconstructed with the hardware imperfection model exhibited smaller artifacts.
The proposed method was particularly effective in reducing artifacts in frequency difference EIT imaging.
Demonstrated the ability to distinguish genuine measurement variations from hardware-induced errors.

Conclusions:

Integrating hardware imperfection models significantly reduces artifacts in EIT images.
The developed method enhances the accuracy and reliability of EIT imaging.
This approach is crucial for improving the clinical applicability of EIT.