Electrical Impedance Tomography for head-brain imaging based on iteratively reweighted least squares (IRLS) algorithm

Electrical Impedance Tomography (EIT) is a non-invasive measurement technique to obtain reconstructed images based on impedance properties. The use of EIT in the medical field has been widely applied including in the detection of brain abnormalities. In this study, EIT was developed for head-brain imaging in which particularly to detect abnormalities in the brain and it was simulated with Electrical Impedance Tomography and Diffuse Optical Tomography Reconstruction Software (EIDORS). There are three processes carried out in the reconstruction of the head-brain image. These processes are namely determining the Finite Element Method (FEM) model and creating strange objects or anomaly inclusion, applying the IRLS algorithm to obtain an inversion solution, and segmenting the anomaly inclusion with k-means clustering. The results of EIT image reconstruction and evaluation with Structural Similarity Indices (SSIM) and Image Correlation Coefficient (ICC) show that the proposed method is able to obtain head-brain images with promising results.