Abstract
A novel image reconstruction method called multiple regression fitting electrical impedance spectro-tomography (mrf-EIST) has been proposed in order to realize the quantitative image reconstruction of dead cell fraction ϕd and cell concentration cc in a huge amount of cell environment. mrf-EIST statistically selects frequencies to extract two variables ψd and ψc, which quantifyϕd and cc, respectively. The ϕd and cc images are reconstructed by solving the inverse problem using ψd and ψc. To validate the performance of mrf-EIST, the image reconstruction by mrf-EIST in the frequency range from 100 Hz to 1 MHz is carried out under the condition that the number of cells is over 109 cells. As a result, mrf-EIST shows that the image quality defined by the difference in pixel value from the true image is less than 0.050 in ϕd and 0.071 in cc, respectively. In comparison to frequency-difference EIT (fd-EIT) as a conventional EIST regarding a position error of center of gravity, mrf-EIST provides much more accurate images, qualitatively and quantitatively, compared to the fd-EIT.
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