Selective Addressingof Versatile Nanodiamonds <i>via</i> Physically-EnabledClassifier in Complex Biosystems

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.

Publication Details

Journal
Figshare
Published
2025-03-14
DOI
https://doi.org/10.1021/acs.nanolett.4c06567.s001
Citations
1
Primary Topic
Diamond and Carbon-based Materials Research
Type
article
Field-Weighted Citation Impact
0.52
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article

Selective Addressingof Versatile Nanodiamonds via Physically-EnabledClassifier in Complex Biosystems

1 citations
Figshare
Diamond and Carbon-based Materials Research
0.52
article

Selective Addressingof Versatile Nanodiamonds via Physically-EnabledClassifier in Complex Biosystems

article en
1 citations

Abstract

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.

Figshare
Openalex Percentile: Top 29%
Diamond and Carbon-based Materials Research
0.52
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Selective Addressingof Versatile Nanodiamonds <i>via</i> Physically-EnabledClassifier in Complex Biosystems · Figshare (2025) | TGRS Research Map | TGRS