Phase imaging with an untrained neural network
This paper introduces PhysenNet, a physics-informed neural network for phase imaging that doesn't require prior training. By integrating the physics of diffraction into the network architecture, PhysenNet can recover phase information from a single diffraction pattern, eliminating the need for extensive labeled training data.