Tissue parameter reconstruction based on an analytical model for a shielded birdcage coil in quantized CSI-EPT

Abstract

Accurate knowledge of the conductivity and permittivity of tissue is vital in the diagnosis of many diseases. Magnetic resonance electrical property tomography (MR-EPT) reconstructs these using measurements of the electromagnetic fields inside the MR-scanner. These properties
re reconstructed using two-dimensional contrast source inversion, due to a significant complexity reduction in comparison to its three-dimensional counterpart, allowing for reconstructions in a reasonable amount of time. Data acquisition is usually performed using a shielded
irdcage coil. Current methods, however, disregard the presence of this shielding, only accounting for it using a rough first-order approximation, as properly accounting for it would lead to an intractable computational load. This thesis shows a method of analytically describing this
hielding in the Greens functions and its efficient implementation in the corresponding Greens operators for CSI-EPT, exploiting the Greens functions being degenerate. This results in a significant increase in the reconstruction performance both qualitatively and quantitatively, at the cost of a slight increase of the computational load. The inversion problem being ill-posed leads to poor reconstruction performance on noisy data. This thesis presents a method for quantization of the tissue parameters, by enforcing a multi-modal distribution for these parameters.
through simulation, the quantization method shows a significant increase in performance for noisy data, at the cost of losing smaller details in the image. This improved model was tested on synthetic E-polarized data, and realistic three-dimensional data, showing a more robust, and
accurate reconstruction of the electrical properties for both.