Generative adversarial network enhances reconstruction quality in magnetic particle imaging, indicating improved performance without hardware changes.
These results validate TSMPI-Net as a practical sequence-aware, end-to-end reconstruction approach for time-series MPI, which enhances overall spatiotemporal reconstruction quality without requiring modifications to MPI hardware or acquisition protocols.
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Gao et al. (2026) studied this question.
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