Quantitative rFRC-based evaluation of computational resolution enhancement in in vivo two-photon subcellular imaging

Intravital imaging with conventional microscopy faces major technical barriers, including limited spatial resolution, high background noise, and motion artifacts caused by physiological activity such as respiration and heartbeat. To visualize subcellular structures such as mitochondria and dynamic processes like autophagy in vivo, we developed an integrated imaging framework that combines two-photon microscopy with tissue stabilization, denoising, and a computational resolution enhancement algorithm. This approach enables high-fidelity visualization of fine intracellular features in living tissues, revealing structural details that typically remain obscured in standard intravital imaging. By improving both signal quality and spatial precision, the platform expands the capacity of in vivo microscopy to investigate rapid organelle dynamics and stress-induced cellular responses.