3D fluorescence imaging with diffuser endoscopy and physics-informed deep learning

Miniaturized endoscopes offer a high potential for biomedical imaging applications. However, conventional fiberoptic endoscopes require lens systems which are not suitable for real-time 3D imaging. Instead, a diffuser is utilized for passively encoding incoherent 3D objects into 2D speckle patterns. For computational image reconstruction beyond the optical memory effect in a spatially varying system, a physics-informed neural network is employed. For the first time worldwide, we demonstrate single-shot 3D incoherent fiber imaging with keyhole access at video rate. The diffuser fiber endoscope can be applied for fluorescence imaging which is promising for in vivo deep brain diagnostics with cellular resolution.