Breast Imaging with Electrical Impedance Tomography: a comparison of traditional Quadratic regularization, Total Variation regularization and Level Set Method on in vivo data

Image Reconstruction in Electric Impedance Tomography (EIT) is an ill-posed problem and regularization techniques are needed in order to obtain meaningful images. Though these techniques allows successful reconstruction, they limit the spatial resolution into the reconstructed image. The ability of reconstruction fast spatial transition in the reconstructed conductivity is important in various clinical applications of EIT. In the context of breast imaging and cancer detection, the use of algorithms capable of reconstructing sharp transitions is important as typically one wishes to detect a small cancerous mass, with electrical properties that differ from the background. Traditionally, in EIT, the image reconstruction is formulated as: