Disaggregated low-field magnetic resonance imaging with secure metasurfaces-enhanced private wireless network

Abstract

The technology described herein is directed towards using a trained artificial intelligence (AI) model to generate high-resolution images from lower resolution magnetic resonance imaging (MRI) images captured by a lower magnetic field strength MRI device. For security and privacy, a reconfigurable intelligent surface can be used in the signal path to the trained model to thwart potential eavesdroppers. Also described is a trained AI annotator model that produces annotation data for annotating a generated high-resolution image. Local training using a cycle generative adversarial network, and based in part on federated learning, provides a highly-accurate low-resolution-to-high-resolution image generator model, while a conditional generative adversarial network provides a highly-accurate annotator model. A medical expert can thus analyze the highly-accurately generated high-resolution images with the benefit of annotation data to highlight any defects detected by the annotator model.