Comb EMI: a hardware-free, training-free approach to EMI correction

Motivation: Point-of-care MRI systems need electromagnetic interference (EMI) cancellation with limited passive shielding to improve cost and portability. Existing methods require external hardware or training, which increases costs and design complexity. Goal(s): This novel solution targeting narrowband EMI is hardware-free, training-free, introduces no white-noise and can be used in conjunction with other methods. Approach: Exploiting the sparsity, L1-regularized compressed sensing is used to extract EMI from a comb-shaped sampling window that consists of noise-dominated regions in acquisition. Results: With proof-of-concept implementation, robust EMI cancellation is demonstrated on both simulated and experimental data, with comparable performance to collector-based method despite the lack of extra hardware. Impact: Point-of-care MRI systems can further push SNR and save scan time by removing narrowband EMI without the cost of additional hardware or training data, enabling new design possibilities for fast, portable, and economically accessible MRI.