Electrical impedance tomography (EIT) calculates images of the body from body impedance measurements. While the spatial resolution of these images is relatively low, the temporal resolution of EIT data can be high. Most EIT reconstruction algorithms solve each data frame independently, although Kalman filter algorithms track the image changes across frames. This paper proposes a new approach wh...

Abstract Electrical Impedance Tomography (EIT) is a imaging method that estimates conductivity distribution inside a body (domain). In this method, images are obtained by applying a sequence of low intensity electrical currents, through electrodes positioned around the body. Applications of EIT can be often found in geophysics sciences, non-destructive testing and medical applications. Although...

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...

We consider the inverse problem of finding cavities within some body from electrostatic measurements on the boundary. By a cavity we understand any object with a different electrical conductivity than the background material of the body. We survey two algorithms for solving this inverse problem, namely the factorization method and a MUSIC-type algorithm. In particular, we present a number of nu...

In this work we study localized electric potentials that have an arbitrarily high energy on some given subset of a domain and low energy on another. We show that such potentials exist for general L∞ + -conductivities in almost arbitrarily shaped subregions of a domain, as long as these regions are connected to the boundary and a unique continuation principle is satisfied. From this we deduce a ...

Electrical impedance tomography has been described as a new method of monitoring critically ill patients on mechanical ventilation. It has recently gained special interest because of its applicability for monitoring ventilation and pulmonary perfusion. Its bedside and continuous implementation, and the fact that it is a non-ionizing and non-invasive technique, makes it an extremely attractive m...

Abstract: EIT can image the distribution of ventilated lung tissue, and is thus a promising technology to help monitor patient breathing to help selection of mechanical ventilation parameters. Two key di culties in EIT instrumentation make such monitoring di cult: 1) EIT data quality depends on good electrode contact and is sensitive to changes in contact quality, and 2) EIT electrodes are di c...

In this article, the following electrical impedance tomography problem (EIT) is considered: On the surface of a body with unknown impedance distribution, one applies a set of prescribed electric currents and measures the corresponding voltages on the surface. From this information, one seeks to estimate the internal structure of the body. Potential application areas of the EIT range from medica...

A new reconstruction algorithm is presented for eit in dimension two, based on the constructive uniqueness proof given by Astala and Päivärinta in [Ann. of Math. 163 (2006)]. The method is non-iterative, provides a noiserobust solution of the full nonlinear eit problem, and applies to more general conductivities than previous approaches. In particular, the new algorithm applies to piecewise smo...

Mechanical ventilation in acute respiratory distress syndrome (ARDS) incurs a risk of ventilator-associated lung injury (VALI) from inhomogeneous conditions and different properties of dependent and non-dependent lung regions at risk of atelectasis and overdistension, respectively. Electrical impedance tomography (EIT) offers regional ventilation assessment to optimise treatment with mechanical...