Deep learning acceleration and reconstruction for single-channel signals

The capacity of the deep learning ReconNet3D model for single-channel image reconstruction with highly under-sampled k-spaces is demonstrated. Without the need for coil sensitivity information, the proposed method can achieve an acceleration factor of 4 on a dual-channel VTC coil. Supporting high-factor acceleration with limited coil channels can be very beneficial for imaging with surface coils or preclinical animal scans.