Development of image reconstruction algorithms for three dimensional magnetic resonance-electrical impedance tomography

Abstract

The electrical resistivity of biological tissues differ among various tissue types. Human body has a large resistivity contrast between a wide range of its tissues. The aim of this study is to reconstruct conductivity images of three dimensional objects with higher resolution and better accuracy than existing conductivity imaging techniques. In order to achieve our goal, we proposed a technique named as Magnetic Resonance - Electrical Impedance Tomography (MR-EIT) which combines the peripheral voltage measurements of classical Electrical Impedance Tomography (EIT) technique with magnetic flux density measurements acquired using a Magnetic Resonance Imaging (MRI) scanner. Five reconstruction algorithms are proposed and computer simulations are made. The proposed algorithms fall in two categories those that utilize current density data and those that utilize magnetic flux density data directly. The first group of algorithms get the current density data from magnetic flux density by Ampere’s law. For calculation of current density with Ampere’s law, we need to all three components of magnetic flux density but that is not possible to get all of them in one measurement phase. Total of three measurement phases are needed for getting all of them but this is not practical because, for measurement of each component the object has to be rotated appropriately in the MRI scanner. The algorithms in the second group suggest an exit to this difficulty and achieve the conductivity reconstruction by using only the data which was acquired in one measurement phase. As can be seen in the results, conductivity reconstruction of three dimensional objects on tomographic planes are made successfully with all of the algorithms. They also work fine against to the measurement noise up to an acceptable level.