Jeong-Rock Yoon

Magnetic resonance electrical impedance tomography (MREIT): simulation study of J-substitution algorithm

We developed a new image reconstruction algorithm for magnetic resonance electrical impedance tomography (MREIT). MREIT is a new EIT imaging technique integrated into magnetic resonance imaging (MRI) system. Based on the assumption that internal current density distribution is obtained using magnetic resonance imaging (MRI) technique, the new image reconstruction algorithm called J-substitution algorithm produces cross-sectional static images of resistivity (or conductivity) distributions. Computer simulations show that the spatial resolution of resistivity image is comparable to that of MRI. MREIT provides accurate high-resolution cross-sectional resistivity images making resistivity values of various human tissues available for many biomedical applications.

Reconstruction of conductivity and current density images using only one component of magnetic field measurements

Magnetic resonance current density imaging (MRCDI) is to provide current density images of a subject using a magnetic resonance imaging (MRI) scanner with a current injection apparatus. The injection current generates a magnetic field that we can measure from MR phase images. We obtain internal current density images from the measured magnetic flux densities via Amperes law. However, we must rotate the subject to acquire all of the three components of the induced magnetic flux density. This subject rotation is impractical in clinical MRI scanners when the subject is a human body. In this paper, we propose a way to eliminate the requirement of subject rotation by careful mathematical analysis of the MRCDI problem. In our new MRCDI technique, we need to measure only one component of the induced magnetic flux density and reconstruct both cross-sectional conductivity and current density images without any subject rotation.

On a nonlinear partial differential equation arising in Magnetic Resonance Electrical Impedance Tomography

This paper considers the fundamental questions, such as existence and uniqueness, of a mathematical model arising in the MREIT system, which is an electrical impedance tomography technique integrated with magnetic resonance imaging. The mathematical model for MREIT is the Neumann problem of a nonlinear elliptic partial differential equation

Three-dimensional forward problem in magnetic resonance electrical impedance tomography (MREIT)

\nabla\cdot(\frac{a(x)}{|\nabla u(x)|}\nabla u(x))=0

Magnetic resonance electrical impedance tomography (MREIT): phantom experiments for static resistivity images using J-substitution algorithm

. We show that this Neumann problem belongs to one of two cases: either infinitely many solutions exist or no solution exists. This explains rigorously the reason why we have used the modified model in [O. Kwon, E. J. Woo, J. R. Yoon, and J. K. Seo, IEEE Trans. Biomed. Engrg., 49 (2002), pp. 160--167], which is a system of the Neumann problem associated with two different Neumann data. For this modified system, we prove a uniqueness result on the edge detection of a piecewise continuous conductivity distribution.

Anomaly detection using impedance measurements on the boundary

In MREIT, we reconstruct cross-sectional resistivity images of a subject. Injecting currents through surface electrodes, we measure internal magnetic flux density using MRCDI technique. Current density can be obtained from the magnetic flux density data. For resistivity image reconstruction algorithms, we need a three-dimensional forward solver computing voltage, current density, and magnetic flux density within the subject. Given injection currents as boundary conditions, the three-dimensional forward solver described in this paper calculates voltage and current density using FEM. Then, it computes the induced magnetic flux density within the subject using the Biot-Savart law.

A real time algorithm for the location search of discontinuous conductivities with one measurement

Lately, a new static resistivity image reconstruction algorithm is proposed utilizing internal current density data obtained by the magnetic resonance current density imaging (MRCDI) technique. This new imaging method is called magnetic resonance electrical impedance tomography (MREIT). In this paper, we present experimental procedures, denoising techniques, and image reconstructions using a 0.3 Tesla experimental MREIT system and saline phantoms. MREIT using J-substitution algorithm effectively utilizes the internal current density information resolving the problem inherent in a conventional EIT, that is, the low sensitivity of boundary measurements to any changes of internal tissue resistivity values.

A NUMERICAL METHOD FOR CAUCHY PROBLEM USING SINGULAR VALUE DECOMPOSITION

We describe a new anomaly detection algorithm based on an electrical impedance tomography (EIT) technique. When only the boundary current and voltage measurements are available, it is not practically feasible to reconstruct accurate high-resolution cross-sectional resistivity images of a subject. In this paper, we focus our attention on the detection of the location and size of anomalies with resistivity values different from the background tissues. We show the performance of the algorithm from experimental results using a 32-channel EIT system and saline phantoms. The algorithm is applicable to the detection of cancerous tissues in the breast.