Use of Adaptive Diffusion Filters to Estimate In-Vivo Conductivity Images from B1+ Maps

Computing electrical conductivity or electrical permittivity maps from the measured B1 maps is a noise-amplifying process due to the Laplacian computation involved in solving the underlying electromagnetic field equations. We applied adaptive diffusion filters (ADFs) to denoise the B1 maps prior to the ordinary Laplacian computation based on the second-order difference equation on three consecutive neighboring pixels in each direction. Both in the simulations and in-vivo conductivity imaging experiments at 3T, we observed significant improvements in the conductivity image quality computed from the noisy B1 maps acquired by the double angle method (DAM).

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