Parallel Imaging

Parallel imaging accelerates magnetic resonance imaging (MRI) acquisition by simultaneously acquiring data from multiple receiver coils, reducing scan times. Current research focuses on improving image reconstruction from this undersampled data, employing techniques like implicit neural representations, generative adversarial networks (GANs), and unrolled optimization networks, often incorporating physical priors from the MRI physics to enhance accuracy and robustness. These advancements are crucial for reducing scan times in MRI, improving patient comfort, and enabling faster and more efficient clinical workflows.