Application of New Algorithms of Electrical Impedance Tomography in Biomedicine

This paper describes an usage of new techniques to solve an electrical impedance tomography (EIT) inverse problem in the biomedical engineering. Usually, a set of voltage measurements is acquired from the boundaries of an investigated volume, whilst this is subjected to a sequence of low-frequency current patterns. In principle, measuring both the amplitude and the phase angle of the voltage can result in images of the electric conductivity and permittivity in the interior of a body. It is well known that while the forward problem is well-posed, the inverse problem is nonlinear and highly ill-posed. The recently described methods are based on deterministic or stochastic approach to solve mainly 2D problems. The aim of this paper is to introduce new techniques of reconstruction of EIT images for their using in a biomedicine. New techniques, which make use of combination of well known methods for reconstruction EIT images (Total Variation Method and Tikhonov Regularization Method) and method used for image segmentation. This way enable exactly specify boundaries of an area with a known conductivity. In this paper are used new techniques for a specification of a human tissue, based on the tissue conductivity. Numerical results of the reconstruction based on new methods are presented and compared.