A Regularized Model-Based Approach to Phase-Based Conductivity Mapping
Kathleen M Ropella 1 and Douglas C Noll 1
Biomedical Engineering, University of
Michigan, Ann Arbor, MI, United States
Phase-based conductivity mapping makes use of a noise
amplifying operation and often relies on spatial
filtering to reduce noise. This work describes a
regularized, model-based approach to conductivity
mapping, which is more robust in the presence of noisy
phase maps and provides better reconstruction near
boundaries. We demonstrate the efficacy of the algorithm
in simulations as well as in the human brain at 3.0T.
This method provides higher SNR and lower RMSE for
reconstructed conductivity maps as compared to a basic
spatial filtering approach.
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