Deep learning-enabled high-performance multiphoton fluorescence vascular imaging using clinically approved fluorescent probes.

Among various modalities, multiphoton fluorescence imaging (MPFI) stands out for its exceptionally high spatial resolution in deep tissue imaging. Unfortunately, current clinically approved fluorescent probes are not engineered for MPFI, hindering the entry of MPFI into the clinical stage. Although several high-performance customized multiphoton probes have been developed, their biosafety has yet to be corroborated. To address this concern, we developed a deep learning-based method, trained on previously reported MPFI images enabled by aggregation-induced emissions luminogens nanoparticles, for high-performance MPFI using commercial q800 quantum dots and a clinically approved indocyanine green (ICG) probe. Remarkably, the proposed method demonstrated exceptional effectiveness when handling previously unseen data and showed strong optimization performance for MPFI images of cerebral microvasculature. Especially, blood vessels in the hippocampus region become clear and noise free after deep learning processing. Overall, this work offers a valuable strategy to greatly improve the practicality and applicability of MPFI.