When designing microscopes, optical engineers have long faced a trade-off between speed, field of view and resolution. But improving one of these properties typically comes at the expense of another.

Researchers designed a computational framework that consists of a compact metalens-integrated microscope and a transformer-based neural network, which enables large FOV and subpixel resolution imaging ...