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Updated: Jun 20, 2026

High-Speed Ultraviolet Photoacoustic Microscopy for Histological Imaging with Virtual-Staining assisted by Deep Learning

High-Speed Ultraviolet Photoacoustic Microscopy for Histological Imaging with Virtual-Staining assisted by Deep Learning

Published on: April 28, 2022

Volumetric localization microscopy with deep learning.

Keyi Han^1,2, Xuanwen Hua^1,2, Tianrui Qi^1,3

¹Laboratory for Systems Biophotonics, Georgia Institute of Technology, Atlanta, GA, USA.

Nature Communications

|December 8, 2025

Summary

This summary is machine-generated.

Volumetric localization microscopy (VLM) with deep learning achieves high-fidelity 3D single-molecule imaging. This super-resolution technique offers hardware simplicity and data efficiency for advanced biomedical research.

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Area of Science:

Biophysics
Optical Microscopy
Computational Biology

Background:

Super-resolution microscopy, especially localization-based methods, faces challenges in balancing optical complexity, computational load, and user accessibility.
Current approaches often use deterministic or learning-based methods separately, missing synergistic potential.

Purpose of the Study:

To introduce volumetric localization microscopy (VLM) with deep learning for high-fidelity 3D single-molecule imaging.
To integrate instrumental and algorithmic innovations for improved super-resolution microscopy.

Main Methods:

VLM utilizes a wavefront-optimized light-field configuration for single-molecule data acquisition.
A cascaded neural network reconstructs 3D volumes and determines molecular coordinates.
The system is trained using system-aware intrinsic point-spread functions, eliminating the need for external modalities or sample-specific data.

Main Results:

Achieved 10 nm lateral and 25 nm axial localization precision.
Demonstrated effective imaging depth over 4 µm.
Validated across diverse biological specimens, showing hardware simplicity, data efficiency, and minimal phototoxicity.

Conclusions:

VLM with deep learning offers a powerful, accessible super-resolution technique for 3D single-molecule imaging.
This method overcomes limitations of current fluorescence microscopy, paving the way for broader biomedical research advancements.