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Multiphoton Intravital Imaging for Monitoring Leukocyte Recruitment during Arteriogenesis in a Murine Hindlimb Model

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Deep learning-based high-speed, large-field, and high-resolution multiphoton imaging.

Zewei Zhao¹, Binglin Shen¹, Yanping Li¹

¹Key Laboratory of Optoelectronic Devices and Systems of Guangdong Province and Ministry of Education, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China.

Biomedical Optics Express

|January 26, 2023

Summary

This summary is machine-generated.

This study introduces a novel AI network to significantly improve multiphoton microscopy for tumor analysis. The technology enhances image resolution and speed, overcoming previous limitations in pathological imaging.

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Area of Science:

Biomedical Imaging
Computational Pathology
Artificial Intelligence in Medicine

Background:

Multiphoton microscopy is crucial for tumor pathological analysis.
Existing systems face limitations in achieving high imaging speed and resolution simultaneously.
Nonlinear optical processes in microscopy have inherent efficiency constraints.

Purpose of the Study:

To develop an advanced computational method for enhancing multiphoton microscopy.
To overcome the trade-off between imaging speed, resolution, and field of view.
To improve the quality of pathological analysis in tumor environments.

Main Methods:

A self-alignment dual-attention-guided residual-in-residual generative adversarial network was developed.
The network was trained using a diverse dataset of multiphoton microscopy images.
The approach focused on enhancing image contrast, spatial resolution, and noise reduction.

Main Results:

The AI network successfully enhanced image contrast and spatial resolution.
Noise and scanning fringe artifacts were significantly suppressed.
The method eliminated the mutual exclusion between field of view, image quality, and imaging speed.

Conclusions:

The developed AI network offers a significant advancement for multiphoton microscopy.
This technology can be integrated into commercial microscopes for improved tumor studies.
It enables large-scale, high-resolution, and low photobleaching investigations of tumor microenvironments.