In electrical impedance tomography (EIT), various image reconstruction algorithms have been used in order to compute the internal resistivity distribution of the unknown object with its electric potential data at the boundary. Mathematically, the EIT image reconstruction algorithm is a nonlinear ill-posed inverse problem. This paper presents a simulated annealing technique as a statistical reco...

This paper presents a static electrical impedance tomography (EIT) technique that evaluates abdominal obesity by estimating the thickness of subcutaneous fat. EIT has a fundamental drawback for absolute admittivity imaging because of its lack of reference data for handling the forward modeling errors. To reduce the effect of boundary geometry errors in imaging abdominal fat, we develop a depth-...

Image Reconstruction in Electric Impedance Tomography (EIT) is an ill-posed problem and regularization techniques are needed in order to obtain meaningful images. Though these techniques allows successful reconstruction, they limit the spatial resolution into the reconstructed image. The ability of reconstruction fast spatial transition in the reconstructed conductivity is important in various ...

Electrical Impedance Tomography (EIT) calculates internal conductivity from surface measurements; image reconstruction is most commonly formulated as an inverse problem using regularization techniques. Regularization adds “prior information” to address the solution ill-conditioning. This paper presents a novel approach to understand and quantify this information. We ask: how many bits of inform...

This paper presents a monotonicity-based spatiotemporal conductivity imaging method for continuous regional lung monitoring using electrical impedance tomography(EIT). The EIT data (i.e., the boundary current-voltage data) can be decomposed into pulmonary, cardiac and other parts using their different periodic natures. The time-differential current-voltage operator corresponding to lung ventila...

Electrical Impedance Tomography (EIT) is a imaging technique that attempts to reconstruct the impedance distribution inside an object from the impedance between electrodes placed at the object’s surface. The EIT reconstruction problem can be approached as a non-linear non-convex optimization problem where one tries to maximize the matching between a simulated impedance problem and the observed ...

To improve the identification of cardiac regions in Electrical impedance tomography (EIT) pulmonary perfusion images, a model of wavelet transform was developed. The main goal was to generate maps of the heart using EIT images in a controlled animal experiment using a healthy pig and in two human volunteers. The model was capable of identifying the heart regions, demonstrated robustness and gen...

Electrical impedance tomography (EIT) aims in reconstructing resistivity distribution of inhomogeneous objects, by using the voltage measurements from the boundary electrodes and facilitates in solving non linear inverse problems. For the medical imaging research community, developing a suitable reconstruction algorithm is a challenging task as the inverse problem in EIT is severely ill-posed. ...

Introduction: To prevention the healthy tissues from irreversible damages, monitoring the temperature variation of healthy tissues is critical parameter during thermal therapies. Electrical impedance tomography (EIT) is considered as a real time imaging modality for monitoring the temperature but researches show that it suffers from low temperature resolution. In this study usi...

A defect sensing method based on electrical impedance spectroscopy is proposed to image cracks and reinforcing bars in concrete structures. The method utilizes the frequency-dependent behavior of thin insulating cracks: low-frequency electrical currents are blocked by insulating cracks, whereas high-frequency currents can pass through thin cracks to probe the conducting bars. From various frequ...