Abstract #5095

Global Maxwell Tomography with Match Regularization for accurate electrical properties extraction from noisy B1+ measurements

Jose E.C. Serralles¹, Athanasios G. Polimeridis², Luca Daniel¹, Daniel K. Sodickson^3,4,5, and Riccardo Lattanzi^3,4,5

¹Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, United States, ²Center for Computational and Data-Intensive Science and Engineering, Skolkovo Institute of Science and Technology, Moscow, Russian Federation, ³Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University School of Medicine, New York, NY, United States, ⁴Bernard and Irene Schwartz Center for Biomedical Imaging (CBI), Department of Radiology, New York University School of Medicine, New York, NY, United States, ⁵Sackler Institute of Graduate Biomedical Sciences, New York University School of Medicine, New York, NY, United States

We introduce a new regularization approach, “Match Regularization”, and show that in tandem with Global Maxwell Tomography (GMT) it enables accurate, artifact-free volumetric estimation of electrical properties from noisy B1+ measurements. We demonstrated the new method for two numerical phantoms with completely different electrical properties distributions, using clinically feasible SNR levels. Estimated electrical properties were accurate throughout the volume for both phantoms. Our results suggest that GMT with match regularization is robust to noise and can be employed to map electrical properties in phantoms and in vivo experiments.

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