Optimization of Radial Diffusion Imaging on a 0.16T Low-Field MRI

Motivation: Low-field MRI systems face challenges in diffusion imaging due to limited gradient strength and switching rates. Overcoming these limits is essential to broaden low-field MRI applications. Goal(s): Develop an advanced, gradient-efficient diffusion imaging sequence and reconstruction algorithm for low-field MRI, aimed at minimizing artifacts and improving image clarity under hardware limitations. Approach: A radial k-space acquisition sequence with Gaussian-based gridding and WOA-optimized iterative L+S decomposition was designed to balance energy distribution and enhance image clarity. Results: This work overcamed limitations of gradient strength and switching rates, enabling diffusion imaging in low-field MRI and demonstrating clear human brain imaging on a 0.16T resistive system. Impact: This work could expand low-field MRI applications, facilitating access to reliable diffusion imaging in primary care settings. Further validation across varied populations may support its broader adoption in resource-limited healthcare environments.