A Parametric Level Set Method for Electrical Impedance Tomography

Abstract

This paper presents an image reconstruction method based on parametric level set (PLS) method using electrical impedance tomography. The conductivity to be reconstructed was assumed to be piecewise constant and the geometry of the anomaly was represented by a shape-based PLS function, which we represent using Gaussian radial basis functions (GRBF). The representation of the PLS function significantly reduces the number of unknowns, and circumvents many difficulties that are associated with traditional level set (TLS) methods, such as regularization, re-initialization and use of signed distance function. PLS reconstruction results shown in this article are some of the first ones using experimental EIT data. The performance of the PLS method was tested with water tank data for two-phase visualization and with simulations which demonstrate the most popular biomedical application of EIT: lung imaging. In addition, robustness studies of the PLS method w.r.t width of the Gaussian function and GRBF centers were performed on simulated lung imaging data. The experimental and simulation results show that PLS method has significant improvement in image quality compared with the TLS reconstruction.

Deep D-Bar: Real-Time Electrical Impedance Tomography Imaging With Deep Neural Networks

“…Our initial testing suggests that this can be improved upon by including significant training on triangular inclusions. Challenges recovering triangular shapes have also been observed in [41]. In terms of image quality, our Deep D-bar approach is comparable to results from (slower) iterative methods on similar data from the KIT4 system, see [9], [34], [41].…”

B-Spline-Based Sharp Feature Preserving Shape Reconstruction Approach for Electrical Impedance Tomography

“…These findings are also supported by the evaluation parameters listed in Table III, the B-spline based approach leads most of those parameters closest to the true values. It is worth noting that reconstructing sharp angular boundaries of the triangular and rectangular-shaped objects is quite challenging in EIT, which has also been observed in [7], [12], [35]. Despite this reality, sharp angular boundaries can be more accurately detected by using the Bspline based approach, which encourages applying B-spline based shape reconstruction method to EIT reconstruction.…”

Artificial Sensitive Skin for Robotics Based on Electrical Impedance Tomography

“…No matter which kind of imaging technologies, it comes down to a problem in mathematics, that is, how to determine the projection of the 2D distribution in a 1D space according to a function of the 2D spatial distribution . This so‐called dimensionality difficulty makes any kind of imaging technologies to encounter the computational instability and error sensitivity .…”