Head Motion Sensing and Estimation in 3D Radial MRI using Region-Optimized Virtual Coil

Motivation: Motion during MRI can severely impact image quality, necessitating advanced techniques to accurately sense and compensate for head movements. Goal(s): This study aims to develop a novel algorithm for high-fidelity motion sensing and position estimation for 3D Radial head scan. Approach: By using Region-Optimized Virtual Coils to move the coil profile and Fourier Slice Theorem to calculate center-of-mass from few spokes, the algorithm detects positional changes and estimates rigid-body motion parameters in high-temporally. Results: Experimental validation using simulated and real datasets demonstrated effective motion detection and significant improvements in image quality, showcasing the method's robustness in motion correction. Impact: This research offers a groundbreaking approach to high-temporal motion sensing in MRI, enhancing image quality through accurate position estimation. It opens avenues for future investigations into motion compensation techniques, ultimately benefiting clinical applications in brain imaging and diagnostics.