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Abstract #5050

Improving Tissue Electrical Properties Reconstructions by Exploiting the Benefits of Combining Deep Learning-EPT and 3D Contrast Source Inversion-EPT

Reijer L. Leijsen1, Cornelis A.T. van den Berg2,3, Rob F. Remis4, Andrew G. Webb1, and Stefano Mandija2,3

1Radiology, Leiden University Medical Center, Leiden, Netherlands, 2University Medical Center Utrecht, Utrecht, Netherlands, 3Utrecht University, Utrecht, Netherlands, 4Circuits and Systems Group, Delft University of Technology, Delft, Netherlands

We propose a two-step approach to EPT reconstruction where we use the results from a deep-learning approach as the initial estimate for a 3D contrast-source inversion algorithm. The combination of these two methods builds upon the strengths of each. Results using an anatomically accurate head model with and without an artificially inserted tumour show that CSI-EPT improves DL-EPT reconstructions in structures that are not present in the training set, while DL-EPT used as an initial guess for CSI-EPT leads to improved accuracy and convergence.

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