Research is being conducted on the use of neural networks to process and reconstruct compromised biophotonic image data. Various approaches are being explored, including the use of recurrent neural networks, deep residual learning, and implicit neural image fields. These methods are being applied to different types of microscopy, such as fluorescence microscopy and scanning microscopy, to improve image quality and enable more effective analysis.