Cellular refractive index and thickness recovery via unsupervised learning framework.

This work presents an AI-driven framework to extract the biological tissue's refractive index and thickness maps from a single RGB image. This approach is based on a physical light-trapping surface and an unsupervised inverse search projector which projects given RGB pixel to the sample's refractive index and thickness at the corresponding coordinate.