Abstract

Electrical Impedance Tomography (EIT) is a non-invasive, inexpensive, and portable medical imaging modality where the patient is probed with electric currents fed through electrodes positioned on the skin. The resulting voltages at the electrodes are measured, and the goal is to recover the internal electric conductivity of the body. The reconstruction task is a highly ill-posed nonlinear inverse problem and requires the use of regularized solution methods. In the so-called D-bar method, one uses a nonlinear low-pass filter to provide regularization. However, this results in a blurry reconstruction that obscures crisp boundaries between tissues. We propose sharpening the EIT image using the diffusive image segmentation of Ambrosio and Tortorelli, controlled by the EIT data vie the so-called CGO sinogram.