Forward Modelling of the Human Thorax for Electrical Impedance Tomography Measurements

Electrical Impedance Tomography (EIT) is a medical imaging technique that reflects the inner conductivity distribution of biological tissue based on boundary voltages measured at the electrodes around the thorax while injecting an alternating current with a low amplitude. In this work, a 16-electrode thorax mesh is implemented for the pyEIT library. This mesh builds the basis for the reconstruction of the conductivity distributions from real human thorax voltage measurements. Post-processing techniques, such as the K-means method and the region based segmentation, have also been implemented. The resulting re-constructed images reflect the conductivity changes during the breathing cycle and by post-processing artifacts are eliminated leading to a clear image of the lungs and the heart.