Transceive Phase Corrected Contrast Source Inversion-Electrical Properties Tomography
P.R.S. Stijnman (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Rob F. Remis – Mentor
Cornelis van den Berg – Mentor
Stefano Mandija – Coach
W.A. Serdijn – Coach
W. Brink – Coach
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Abstract
Electrical properties tomography is the quantification of the conductivity and permittivity of different materials. In an MRI setting this can be used to map the electrical properties of tissue. These values can be used as a different contrast mechanism, for hyperthermia treatment or the improvement of antenna design for specific applications. There are different methods used to obtain these electrical properties, however these often use differential operators on measured data. This leads to reconstructions corrupted by noise, thus in this thesis the work on contrast source inversion based electrical properties tomography is continued. This method uses an integral approach and is therefore more robust with respect to noise.
The work presented continues from the two-dimensional Matlab based simulations and extends these to a more realistic measurement setup. The RF-shield is numerically implemented and an extension is made to the existing algorithm to handle the transceive phase based on Maxwell's equations. This is done by implementing a forward problem into the inverse problem of getting the contrast from the measured radiofrequency field. After this the algorithm was tested with three-dimensional FDTD simulations and finally a phantom study was done to test with an MRI scanner.
From the results of the two-dimensional simulations it was seen that this method is indeed very robust when it comes to a realistic measurement setup. In the three-dimensional simulations it was observed that the electrical properties are underestimated. Nonetheless CSI-EPT is more precise than the standard Helmholtz based methods. Plus the improvement made to the algorithm makes it possible to map all the RF fields inside the scanner which has not been done before. The same underestimation was seen with the reconstruction of the measured data from the phantom study.