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.
The numbers under the feature cubes represent the channel number of the corresponding hidden feature
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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.