Accelerated MRI Reconstruction
Accelerated MRI reconstruction aims to significantly reduce MRI scan times by reconstructing high-quality images from undersampled data. Current research heavily utilizes deep learning, employing various architectures such as transformers, diffusion models, and unrolled networks, often incorporating multi-prior learning and self-supervised training to improve robustness and reduce reliance on fully-sampled data. These advancements hold significant promise for improving patient comfort, enabling faster clinical workflows, and facilitating new applications requiring rapid imaging, such as real-time image-guided interventions.
Papers
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