Multifrequency Electrical Impedance Tomography With Ratiometric Preprocessing for Imaging Human Body Compartments

Reconstructing the structural images of human body compartments as point-of-care imaging could be possible using electrical impedance tomography (EIT), but the reconstructed image deteriorates due to high conductivity contrast
$\mu $
between anomaly and background. In this study, a multifrequency EIT (mf-EIT) with a ratiometric preprocessing (ratiometric EIT) has been developed in order to minimize
$\mu $
while maintaining high distinguishability without any
$a$

priori
information. The preprocessing of ratiometric EIT is achieved by extending the framework of ratiometric methods that uses the ratio of two measurement signals. Based on the proposed ratiometric preprocessing, ratiometric frequency-difference adjacent EIT (rfda-EIT) is newly derived. The rfda-EIT is qualitatively and quantitatively evaluated by numerical simulation under the variant conditions of
$\mu $
(=95%–10%) and experiment with eight subjects’ calves. As the results, the rfda-EIT scores the area ratio error of subcutaneous adipose tissue (SAT) 17.09% < ARE
$^{\mathrm {SAT}} < 28.13$
%, the position error of bone tibia 0.14% < PE
$^{\mathrm {tibia}} < 10.19$
%, the position error of bone fibula 9.51% < PE
$^{\mathrm {fibula}} < 1.74$
%, and the correlation coefficients
$0.79< $
CC < 0.91 in the numerical simulation. The total mean area ratio error
$\langle $
ARE
$^{\mathrm {SAT}}\rangle $
by the rfda-EIT is lower than the error by the classical frequency-difference adjacent EIT (fda-EIT) from 12.70% to 5.18% in the experiment. Moreover, the true positive rate TPR
$^{\mathrm {tibia}}$
for the bone tibia detection by the rfda-EIT is increased from 50.0% to 87.5% compared with the rate by the fda-EIT.