99 / 2021-11-01 13:41:33

Super Resolution of MR via Learning Virtual Parallel Imaging

virtual parallel imaging,Super-Resolution imaging,reversible network

Magnetic resonance imaging (MRI) is a widely used medical imaging modality. However, due to the limitations in hardware, it is often clinically challenging to obtain high-quality MR images. Super-resolution (SR) is potentially promising to improve MR image quality without any hardware upgrade. Instead of the classical SR reconstruction method that enhance the spatial resolution via utilizing the spatial information itself, in this work, we propose a novel SR method via learning channel information in virtual parallel imaging. We use auxiliary variable technology to make the channel number of network output to be equal to the network input, increasing the number of channels information to achieve SR reconstruction. Compared with state-of-the-art SR methods, the present approach is advantageous in generating more details with higher resolution.