MicroEIT Simulation images

Data provide here as supplementary information shows the image results of image reconstruction using traditional imaging methods (GN, JAC) and our trained machine learning models during the development and testing of the 1D-CNN model for the microEIT system. Groundtruch and Python generated random noise images are also provided. Image reconstruction results obtained using our 1D-CNN show significant advantages over the two traditional methods, achieving an up to hundred-fold reduction in mean square error on synthetic data. This was replicated for two common excitation/measurement modes and was extended to objects with different conductivity and of varying quantities.