Sodium MRI can acquire important biological information about cell integrity and tissue viability, but its clinical application has been limited by low SNR and poor spatial resolution. We propose a novel method to reconstruct high-quality sodium images from limited and noisy k-space data. The new method synergistically integrates model-based reconstruction with deep learning. Simulation and experimental results show that the proposed method can reconstruct high-SNR and high-resolution sodium images, which clearly delineate lesions such as brain tumors.
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