Current constrained voltage scaled reconstruction (CCVSR) algorithm for MR-EIT and its performance with different probing current patterns

Abstract

Conventional injected-current electrical impedance tomography (EIT) and magnetic resonance imaging (MRI) techniques can be combined to reconstruct high resolution true conductivity images. The magnetic flux density distribution generated by the internal current density distribution is extracted from MR phase images. This information is used to form a fine detailed conductivity image using an Ohm's law based update equation. The reconstructed conductivity image is assumed to differ from the true image by a scale factor. EIT surface potential measurements are then used to scale the reconstructed image in order to find the true conductivity values. This process is iterated until a stopping criterion is met. Several simulations are carried out for opposite and cosine current injection patterns to select the best current injection pattern for a 2D thorax model. The contrast resolution and accuracy of the proposed algorithm are also studied. In all simulation studies, realistic noise models for voltage and magnetic flux density measurements are used. It is shown that, in contrast to the conventional EIT techniques, the proposed method has the capability of reconstructing conductivity images with uniform and high spatial resolution. The spatial resolution is limited by the larger element size of the finite element mesh and twice the magnetic resonance image pixel size.

Noise Analysis of Current Density Imaging: A Pilot Study

“…Note also that one of the natural applications of MRCDI is to image electrical impedance distribution based on the relationship between the current density and electrical impedance of the tissue [6,[8][9][10][11].…”

Reconstruction of apparent orthotropic conductivity tensor image using magnetic resonance electrical impedance tomography

“…When it is early stage, several conductivity image reconstruction algorithms were developed based on the assumption that the current density J ¼ (J x , J y , J z ) is available from the measured data of B at every pixels. Those methods include the J-substitution algorithm, 4,5 current constrained voltage scaled reconstruction algorithm, 6 and equipotential line methods. [7][8][9] To avoid rotating the imaging object inside a MRI scanner, the latest image reconstruction algorithms in MREIT have focused on producing the isotropic or equivalent isotropic conductivity image using only B z data.…”

Anisotropic WM conductivity reconstruction based on diffusion tensor magnetic resonance imaging: a simulation study

“…The conductivity distribution image can be reconstructed based on the relationship between the conductivity and the measured magnetic flux density combined with the current density. MREIT reconstruction algorithms fall into two categories [10]: those utilizing internal current density [10][11][12][13][14] and those making use of measured magnetic flux density [15][16][17][18][19][20][21][22]. Considering the rotation problem of the object in the MRI system, the latter has the advantage of avoiding the object rotation over the former.…”