  Nitrogen-vacancy (NV) centers show great potentials for nanoscale bio-sensing
and bio-imaging. Nevertheless, their envisioned bio-applications suffer from
intrinsic background noise due to unavoidable light scattering and
autofluorescence in cells and tissues. Herein, we develop a novel all-optical
modulated imaging method via physically-enabled classifier, for on-demand and
direct access to NV fluorescence at pixel resolution while effectively
filtering out background noise. Specifically, NV fluorescence can be modulated
optically to exhibit sinusoid-like variations, providing basis for
classification. We validate our method in various complex biological scenarios
with fluorescence interference, ranging from cells to organisms. Notably, our
classification-based approach achieves almost 10^6 times enhancement of
signal-to-background ratio (SBR) for fluorescent nanodiamonds (FNDs) in neural
protein imaging. We also demonstrate 4-fold contrast improvement in
optically-detected magnetic resonance measurements (ODMR) of FNDs inside
stained cells. Our technique offers a generic, explainable and robust solution,
applicable for realistic high-fidelity imaging and sensing in challenging
noise-laden scenarios.
