Electrical impedance tomography reconstruction using a monotonicity approach based on a priori knowledge

Electrical Impedance Tomography (EIT) has been proposed as an alternative modality for breast imaging. Current EIT reconstruction algorithms are based in optimization procedures that aim to minimize the difference between the recorded data and a set of candidate scenarios. However, these methods produce images with diffused edges, as sharp structures are penalized by current regularization techniques. In this paper, a novel edge preserving EIT reconstruction method is proposed. This technique uses a priori information obtained from Breast Microwave Radar images to estimate the location of the dense breast regions. Then, the monotonicity of the impedance matrix of the collected data is used to reconstruct a profile of the tissue distribution in the breast region. The proposed method yielded promising results when applied to numeric phantoms generated from Magnetic Resonance Imaging datasets.