Tan Yayin, Wang Xiaolu, Xu Feng, Hu Xinhao, Lin Yuan, Gao Bo, Chu Zhiqin
Department of Electrical and Electronic Engineering, the University of Hong Kong, Pok Fu Lam, Hong Kong, China.
School of Biomedical Sciences, Faculty of Medicine, the Chinese University of Hong Kong, Shatin, Hong Kong, China.
Nano Lett. 2025 Apr 9;25(14):5679-5687. doi: 10.1021/acs.nanolett.4c06567. Epub 2025 Mar 14.
Nitrogen-vacancy (NV) centers show great potential for nanoscale biosensing and bioimaging. Nevertheless, their envisioned bioapplications suffer from intrinsic background noise due to unavoidable light scattering and autofluorescence in cells and tissues. Herein, we develop a unique all-optical modulated imaging method via a 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 a 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 an enhancement of signal-to-background ratio from 1.92 to 60.39 dB for fluorescent nanodiamonds in neural protein imaging. We also demonstrate a 4-fold contrast improvement in optically detected magnetic resonance measurements 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.
氮空位（NV）中心在纳米级生物传感和生物成像方面显示出巨大潜力。然而，由于细胞和组织中不可避免的光散射和自发荧光，它们预期的生物应用受到固有背景噪声的影响。在此，我们通过一种物理实现的分类器开发了一种独特的全光调制成像方法，用于在像素分辨率下按需直接获取NV荧光，同时有效滤除背景噪声。具体而言，NV荧光可以通过光学调制呈现出类似正弦的变化，为分类提供了基础。我们在从细胞到生物体的各种具有荧光干扰的复杂生物场景中验证了我们的方法。值得注意的是，我们基于分类的方法在神经蛋白质成像中，将荧光纳米金刚石的信背比从1.92提高到了60.39 dB。我们还展示了在染色细胞内的光学检测磁共振测量中对比度提高了4倍。我们的技术提供了一种通用、可解释且稳健的解决方案，适用于充满挑战的高噪声场景中的实际高保真成像和传感。
