Evaluation of an EIT reconstruction algorithm using finite difference human thorax models as phantoms

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Abstract

A finite difference model of the human thorax with 113 400 control volumes (nodes) based on ECG gated MRI images was used to evaluate the Sheffield DAS-01P EIT system. Sixteen simulated electrode positions equally spaced around the thorax model at approximately the fourth intercostals space level were selected. Pairs of adjacent positions were excited sequentially by injecting current in a manner similar to that used by the Sheffield DAS-01 P EIT system. The resulting voltages on the non-excited electrode positions were calculated and used to reconstruct the image using the Sheffield filtered back projection algorithm. By changing the resistivities of the lungs, the ventricles and the atria over a range of 1% to 40%, the resulting changes in the images were quantified by measuring the average resistivity change over a region defined automatically by two thresholds, 40% or 80% of the average of the first four pixels with the largest change. The results show that the changes observed in the images are consistently less than the changes in the model, but changed in a nearly linear manner as a function of resistivity in the model. For 40% resistivity changes in the model for right lung, right ventricle and right atrium, the observed resistivity changes in the region of interest (ROI, defined by the 80% threshold) of the images are 32% for the right lung, 11% for the right ventricle and 5.5% for the right atrium, which suggests strong volume dependence of EIT imaging. The effect of structural (size) change between end diastole and end systole was also studied, which showed large resistivity changes caused in the heart region of the constructed image. The study demonstrates that the Sheffield DAS-01P EIT reconstruction algorithm tracks the change occurring in the lungs most closely and with proper scaling may be used to observe physiological changes.

Original languageEnglish (US)
Pages (from-to)467-475
Number of pages9
JournalPhysiological Measurement
Volume24
Issue number2
DOIs
StatePublished - May 1 2003

Keywords

  • EIT
  • Electrical impedance tomography
  • Finite difference model
  • Impedance imaging

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