Coil Sensitivity

Coil sensitivity estimation is crucial for accurate magnetic resonance imaging (MRI) reconstruction, particularly in accelerated acquisition techniques that undersample k-space data. Current research focuses on jointly estimating coil sensitivities and the image itself, often employing deep learning models like implicit neural representations or score-based diffusion models, and sometimes avoiding explicit sensitivity map estimation altogether through learned unrolled reconstruction methods. Improved coil sensitivity estimation leads to higher-quality MRI images from faster scans, impacting both clinical diagnostics and research by reducing scan times and improving image fidelity.