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Abstract #3774

New Approaches for Simultaneous Noise Suppression and Edge Preservation to Achieve Accurate Quantitative Conductivity Mapping in Noisy Images

Anita Karsa1 and Karin Shmueli1
1Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom

Due to their extreme noise amplification, current Quantitative Conductivity Mapping (QCM) techniques require high SNR images. Simultaneous Quantitative Susceptibility Mapping and QCM uses low-SNR gradient-echo sequences, creating a need for QCM methods appropriate for noisy images. Here we proposed, optimised, and compared several new QCM methods (all shared on built on the widely-used phase-based formula and its equivalent, less popular integral form. We found that solving the integral equation provided lower errors and better edge preservation in both simulated and in-vivo images, and that edge preservation combining magnitude-based and image-segmentation-based techniques resulted in the best in-vivo conductivity map.

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