Two-Photon Excitation-Based Imaging Postprocessing Algorithm Model for Background-Free Bioimaging.

Bioimaging is a powerful strategy for studying biological activities, which is still limited by the difficulty of distinguishing obscured signals from high background. Despite the development of various new imaging materials and methods, target signals are still likely to be submerged in spontaneous fluorescence or scattering signals. Herein, a novel two-photon excitation-process-based imaging postprocessing algorithm model (2PIA) is introduced to minimize background noise, and triplet-triplet annihilation upconversion metal-organic frameworks (UCMOFs) are chosen as demonstration. Through the collection of several image stacks, the related polynomial of the luminescence intensity and excitation power was established, following splitting the desired signals from noise and obtaining the background-free images definitely. Both in vitro and in vivo experiments show that improved signal visibility is achieved through 2PIA and UCMOFs by removing the interference of scattering, bioluminescence, and other fluorescence materials. The imaging spatial resolution and tissue penetration depth were greatly enhanced. Benefiting from 2PIA, as low as 100 UCMOFs labeled cells can be identified from obscuring background easily after intravenous injection. This image postprocessing method combined with special two-photon excited luminescent materials can conduct biological imaging from complex background interference without using expensive instruments or delicate materials, which holds great promise for accurate biological imaging.