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Abstract #0184

Data-driven Electrical Conductivity Reconstructions via transceive phase and signal magnitude gradient data from the three imaging directions

Chan-Hee Park1, Thierry G. Meerbothe2,3, Kyu-Jin Jung1, Chuanjiang Cui1, Mina Park4, Yoonho Nam5, Cornelis A.T. van den Berg2,3, Stefano Mandija2,3, and Dong-Hyun Kim1
1Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea, Republic of, 2Department of Radiotherapy, Division of Imaging and Oncology, UMC Utrecht, Utrecht, Netherlands, 3Computational Imaging Group for MR Diagnostics and Therapy, UMC Utrecht, Utrecht, Netherlands, 4Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Korea, Republic of, 5Divison of Biomeidcal Engineering, Hankuk University of Foreign Studies, Yongin-Si, Korea, Republic of

Synopsis

Keywords: Electromagnetic Tissue Properties, Electromagnetic Tissue Properties

Motivation: Phase-based conductivity reconstructions suffer from poor structural information and lack of conductivity information from through plane (z-direction) phase variations.

Goal(s): To present an end-to-end process that utilizes gradient information from the transceive phase and tissue magnitude in all three directions (in-plane: x/y and through plane: z) to address the issue of boundary artifacts in conductivity reconstructions and lack of conductivity information from the z-direction.

Approach: This method was trained on simulated data (SNR=50), and tested both on simulated and measured in-vivo data.

Results: This approach reduces boundary errors and shows higher accuracy in conductivity reconstructions compared to conventional methods.

Impact: In contrast to existing tissue conductivity reconstruction algorithms that operate under the assumption of negligible through-plane (z) transceive phase contributions, our approach demonstrates enhanced efficacy and more accurate conductivity reconstructions by explicitly considering through-plane phase variations.

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Keywords