SUSEP-Net is a simulation-trained dual-branch U-net with contrastive learning that separates QSM into paramagnetic and diamagnetic source maps, outperforming three existing methods in reported experiments.
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SUSEP-Net: Simulation-Supervised and Contrastive Learning-based Deep Neural Networks for Susceptibility Source Separation
SUSEP-Net is a simulation-trained dual-branch U-net with contrastive learning that separates QSM into paramagnetic and diamagnetic source maps, outperforming three existing methods in reported experiments.