Robust Electromagnetic Interference (EMI) Elimination for RF Shielding-Free MRI via Active EMI Sensing and Deep Learning MRI Signal Prediction

MRI scans are commonly performed inside a fully-enclosed RF shielding room, posing stringent installation requirement and unnecessary patient discomfort. This study develops a strategy of active EMI sensing and deep learning MR signal prediction using residual U-Net for RF shielding-free MRI. We implemented it on an ultra-low-field 0.055T head MRI scanner. Our experimental results demonstrated that this strategy could directly and accurately predict EMI-free MRI signals from the signals acquired by MRI receive coil and EMI sensing coils. It worked robustly with strong and dynamically varying EMI sources, yielding significantly improved brain image quality.