Diffuser endoscopy for single-shot fluorescence imaging using physics-informed deep learning (Invited Paper)

Minimally invasive endoscopy using multicore fibers shows great potential for numerous applications in biomedical imaging. With a diffuser on the distal side of the fiber and image recovery using AI, single-shot 3D imaging is possible by encoding the image volume into 2D speckle patterns. In comparison to equivalent lens systems, a higher space-bandwidth product can be achieved. However, decoding the image with iterative algorithms is time-consuming. Thus, we propose utilizing a neural network for fast 2D and 3D image reconstruction at video rate. In this work, single-shot 3D fluorescence imaging with physics-informed neural network is presented, which is promising for calcium imaging at in vivo brain diagnostics.