Integrating AI-assisted image enhancement with physics-based synthesis of low-field MRI from high-field MRI

The proposed framework addresses key limitations hindering the broader adoption of low-field MRI, including noise, artifacts, and resolution loss inherent to low-field acquisitions. By integrating deep learning with physics-based simulations, the approach achieves notable qualitative and quantitative enhancements in denoising, artifact removal, and overall image quality. These results highlight the framework's potential to improve the practical utility of low-field MRI substantially.