CNNT denoising for cine imaging at 0.55T with higher acceleration rates

Low field MRI systems are promising to increase the accessibility of cardiac MRI, at the expense of lower SNR. Here, we present the application of a g-factor-savvy denoising for cine imaging at 0.55T to increase useable acceleration rate. We used a model that combines convolutional neural networks and transformer model. The denoising network uses complex 2D+time images in SNR-units and g-factor maps as inputs and was trained with 3T data. The percent mean myocardial SNR gain at 0.55T across 9 healthy volunteers was 97±31% (R=2) and 122±22% (R=3), with no indication of overt temporal or spatial smoothing.