Phantoms are essential for assessing the system performance in Electrical Impedance Tomography (EIT). Saline phantoms with insulator inhomogeneity fail to mimic the physiological structure of real body tissue in several aspects. Saline or any other salt solution is purely resistive and hence studying multifrequency EIT systems cannot be assessed with saline phantoms because the response of the purely resistive materials do not change over frequency. Animal tissues show a variable response over a wide band of signal frequency due to their complex physiological and physiochemical structures and hence they can be suitably used as bathing medium and inhomogeneity in the phantoms of multifrequency EIT systems. An efficient assessment of a multifrequency EIT system with a real tissue phantom needs a prior knowledge of the impedance profile of the bathing medium as well as the inhomogeneity. In this direction Electrical Impedance Spectroscopy (EIS) studies on broiler chicken muscle tissue paste, muscle tissue blocks and fat tissue blocks are conducted over a wide range of signal frequency using impedance analyzers, and their impedance profiles are analyzed. Results show that the chicken muscle tissue paste is less resistive than the fat tissue and hence it can be used successfully as the bathing medium of the phantoms for impedance imaging in multifrequency EIT. Fat tissue is found more resistive than the muscle tissue which makes it more suitable for the inhomogeneity in phantoms of impedance imaging study. Moreover, as there is a large difference between the resistivities of muscle tissue and fat tissue they can be used as either inhomogeneity or background medium. EIS studies also show that the variations in the impedance parameters of a muscle tissue block are greater than in the tissue paste as the cell membrane structures are destroyed in tissue paste. Results also show that the α and β dispersions are visible in all the parameters of both the tissue samples, but both the dispersions are larger in the muscle tissue block. The Nyquist plot obtained for the muscle tissue block demonstrates that the equivalent electric model of the tissue sample contains Warburg impedance and a constant phase element.
Tushar Kanti Bera, Samir Kumar Biswas, K. Rajan and J. Nagaraju
A Projection Error Propagation-based Regularization (PEPR) method is proposed and the reconstructed image quality is improved in Electrical Impedance Tomography (EIT). A projection error is produced due to the misfit of the calculated and measured data in the reconstruction process. The variation of the projection error is integrated with response matrix in each iteration and the reconstruction is carried out in EIDORS. The PEPR method is studied with the simulated boundary data for different inhomogeneity geometries. Simulated results demonstrate that the PEPR technique improves image reconstruction precision in EIDORS and hence it can be successfully implemented to increase the reconstruction accuracy in EIT.
Tushar Kanti Bera, Samir Kumar Biswas, K. Rajan and J. Nagaraju
A Block Matrix based Multiple Regularization (BMMR) technique is proposed for improving conductivity image quality in Electrical Impedance Tomography (EIT). The response matrix (JTJ) has been partitioned into several sub-block matrices and the largest element of each sub-block matrix has been chosen as regularization parameter for the nodes contained by that sub-block. Simulated boundary data are generated for circular domains with circular inhomogeneities of different geometry and the conductivity images are reconstructed in a Model Based Iterative Image Reconstruction (MoBIIR) algorithm. Conductivity images are reconstructed with BMMR technique and the results are compared with the Single-step Tikhonov Regularization (STR) and modified Levenberg-Marquardt Regularization (LMR) methods. Results show that the BMMR technique improves the impedance image and its spatial resolution for single and multiple inhomogeneity phantoms of different geometries. It is observed that the BMMR technique reduces the projection error as well as the solution error and improves the conductivity reconstruction in EIT. Results also show that the BMMR method improves the image contrast and inhomogeneity conductivity profile by reducing background noise for all the phantom configurations.
Tushar Kanti Bera, Nagaraju Jampana and Gilles Lubineau
Under an alternating electrical signal, biological tissues produce a complex electrical bioimpedance that is a function of tissue composition and applied signal frequencies. By studying the bioimpedance spectra of biological tissues over a wide range of frequencies, we can noninvasively probe the physiological properties of these tissues to detect possible pathological conditions. Electrical impedance spectroscopy (EIS) can provide the spectra that are needed to calculate impedance parameters within a wide range of frequencies. Before impedance parameters can be calculated and tissue information extracted, impedance spectra should be processed and analyzed by a dedicated software program. National Instruments (NI) Inc. offers LabVIEW, a fast, portable, robust, user-friendly platform for designing data-analyzing software. We developed a LabVIEW-based electrical bioimpedance spectroscopic data interpreter (LEBISDI) to analyze the electrical impedance spectra for tissue characterization in medical, biomedical and biological applications. Here, we test, calibrate and evaluate the performance of LEBISDI on the impedance data obtained from simulation studies as well as the practical EIS experimentations conducted on electronic circuit element combinations and the biological tissue samples. We analyze the Nyquist plots obtained from the EIS measurements and compare the equivalent circuit parameters calculated by LEBISDI with the corresponding original circuit parameters to assess the accuracy of the program developed. Calibration studies show that LEBISDI not only interpreted the simulated and circuit-element data accurately, but also successfully interpreted tissues impedance data and estimated the capacitive and resistive components produced by the compositions biological cells. Finally, LEBISDI efficiently calculated and analyzed variation in bioimpedance parameters of different tissue compositions, health and temperatures. LEBISDI can also be used for human tissue impedance analysis for electrical impedance-based tissue characterization, health analysis and disease diagnosis.