Detecting stochastic inclusions in electrical impedance tomography

Detecting Inclusions in Electrical Impedance Tomography Without Reference Measurements

We develop a new variant of the factorization method that can be used to detect inclusions in electrical impedance tomography from either absolute current-to-voltage measurements at a single, nonzero frequency or from frequency-difference measurements. This eliminates the need for numerically simulated reference measurements at an inclusion-free body and thus greatly improves the method’s robus...

Applications of Electrical Impedance Tomography in Neurology

Introduction: Electrical impedance tomography (EIT) is a non-invasive technique utilized in various medical applications, including brain imaging and other neurological diseases. Recognizing the physiological and anatomical characteristics of organs based on their electrical properties is one of the main applications of EIT, as each variety of tissue structure has its own electrical characteris...

Locating multiple inclusions from sweep data of electrical impedance tomography

Characterization of Inclusions in Impedance Tomography

The inverse problem of electrical impedance tomography (EIT) is to recover the conductivity inside an investigated object from boundary measurements of current and voltage. There is a variety of methods to localize inclusions, i.e. domains in which the conductivity is different from the background conductivity such as e.g. the Factorization method. However, these qualitative methods don’t provi...

Electrical impedance tomography

We review theoretical and numerical studies of the inverse problem of electrical impedance tomography which seeks the electrical conductivity and permittivity inside a body, given simultaneous measurements of electrical currents and potentials at the boundary. (Some figures in this article are in colour only in the electronic version)