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Abstract #3983

Improving Quantitative Susceptibility Mapping reconstructions via non-linear Huber loss data fidelity term (Huber-QSM)

Mathias Gabriel Lambert1,2,3, Carlos Milovic4, and Cristian Tejos1,2,3
1Department of Electrical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile, 2Biomedical Imaging Center, Pontificia Universidad Católica de Chile, Santiago, Chile, 3Millennium Nucleus for Cardiovascular Magnetic Resonance, Santiago, Chile, 4Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom

Compared to L2-norm based QSM reconstructions, methods based on L1-norm data consistency are less prone to artifact generation caused by phase inconsistencies (e.g. unwrapping artifacts, intravoxel dephasing). However, L2-norm methods present better denoising performance in high SNR regions. Here, we present a QSM algorithm that combines the strengths of the L1 and L2 norms, using Huber's loss function as the data consistency term. Simulations and in vivo reconstructions showed enhanced performance, with superior artifact suppression capabilities of our proposed method.

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