Accelerating 7T susceptibility-weighted imaging with complex-valued convolutional neural network

Ultra-high field 7T susceptibility-weighted imaging (SWI) has shown great potential in visualizing and evaluating a broad range of pathology, but suffers from long acquisition times. In this study, a complex-valued convolutional neural network (ComplexNet) model was proposed to reconstruct highly accelerated 7T SWI data. The average reconstruction time of ComplexNet was 0.56 seconds per slice (45.16 seconds per participant). Meanwhile, ComplexNet can provide high-quality 7T SWI for visualizing subtle pathology, including cerebral microbleeds, asymmetric deep medullary veins, and swallow tail sign.