Keywords: Electromagnetic Tissue Properties, Electromagnetic Tissue Properties, MR-EPT, electrical conductivity mapping, electrical properties tomography, noise reduction
Motivation: Phase-based electrical properties tomography calculates conductivities by fitting the transceive phase weighted by a Gaussian function of the magnitude image with width δ. Currently, δ is selected empirically and its impact on conductivities is unknown.
Goal(s): To investigate the effect of δ on conductivity maps and develop a method to automatically select δ.
Approach: After evaluating relationships between δ and healthy brain conductivities at 3T, we calculated conductivities using a voxel-wise δ based on inverse phase noise and compared the results.
Results: Increasing δ decreased contrast and noise in conductivity maps. Our new method to calculate a varying δ automatically optimised conductivity maps.
Impact: We have developed a method to calculate a varying Gaussian weighting width for EPT. This will enable automatic optimisation of conductivity maps rather than time-consuming empirical choice of δ, facilitating the use of phase-based EPT and broadening its applicability.
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