Ultra-low photodamage three-photon microscopy assisted by neural network for monitoring regenerative myogenesis

Abstract Three-photon microscopy (3PM) enables high-resolution three-dimensional (3D) imaging in deeply situated and highly scattering biological specimens, facilitating precise characterization of biological morphology and cellular-level physiology in vivo. However, the use of fluorescent probes with relatively low three-photon absorption cross-sections necessitates high-peak-power lasers for excitation, which poses inherent risks of light-induced damage. Additionally, the low repetition frequency of these lasers prolongs scanning time per pixel, hampering imaging speed and exacerbating the potential for photodamage. Such limitations hinder the application of 3PM in studying vulnerable tissues, including muscle regeneration. To address this critical issue, we developed the Multi-Scale Attention Denoising Network (MSAD-Net), a precise and versatile denoising network suitable for diverse structures and varying noise levels. Our network enables the use of lower excitation power (1/4–1/2 of the common power: 1.0–1.5 mW vs 4–6 mW) and shorter scanning time (1/6–1/4 of the common time: 2–3 μs/pixel vs 12 μs/pixel) in 3PM while preserving image quality and tissue integrity. It achieves a structural similarity index (SSIM) of with an average of 0.9932 and a fast inference time of just 80 ms per frame which ensured both high fidelity and practicality for downstream applications. By utilizing MSAD-Net-assisted imaging, we characterize the biological morphology and functionality of muscle regeneration processes through deep in vivo five-channel imaging under low excitation power and short scanning time, while maintaining a high signal-to-noise ratio (SNR) and excellent axial spatial resolution. Furthermore, we conducted high axial-resolution dynamic imaging of vascular microcirculation, macrophages, and ghost fibers. Our findings provide a deeper understanding of the mechanisms underlying muscle regeneration at the cellular and tissue levels.

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Publication Details

Journal
PhotoniX
Published
2025-10-09
DOI
https://doi.org/10.1186/s43074-025-00191-6
Primary Topic
Muscle Physiology and Disorders
Type
article
Field-Weighted Citation Impact
0.00

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article

Ultra-low photodamage three-photon microscopy assisted by neural network for monitoring regenerative myogenesis

Runnan Zhang, Zheng Zheng, Mubin He, Shuhong Qi et al.
PhotoniX
Muscle Physiology and Disorders
article

Ultra-low photodamage three-photon microscopy assisted by neural network for monitoring regenerative myogenesis

Runnan Zhang, Zheng Zheng, Mubin He, Shuhong Qi, Yifei Li, Jun Qian, Xi Wang, Zichen Wei, Ming Jiang, Keying Li, Chenlin Liang, Xin Xie
article en

Abstract

Abstract Three-photon microscopy (3PM) enables high-resolution three-dimensional (3D) imaging in deeply situated and highly scattering biological specimens, facilitating precise characterization of biological morphology and cellular-level physiology in vivo. However, the use of fluorescent probes with relatively low three-photon absorption cross-sections necessitates high-peak-power lasers for excitation, which poses inherent risks of light-induced damage. Additionally, the low repetition frequency of these lasers prolongs scanning time per pixel, hampering imaging speed and exacerbating the potential for photodamage. Such limitations hinder the application of 3PM in studying vulnerable tissues, including muscle regeneration. To address this critical issue, we developed the Multi-Scale Attention Denoising Network (MSAD-Net), a precise and versatile denoising network suitable for diverse structures and varying noise levels. Our network enables the use of lower excitation power (1/4–1/2 of the common power: 1.0–1.5 mW vs 4–6 mW) and shorter scanning time (1/6–1/4 of the common time: 2–3 μs/pixel vs 12 μs/pixel) in 3PM while preserving image quality and tissue integrity. It achieves a structural similarity index (SSIM) of with an average of 0.9932 and a fast inference time of just 80 ms per frame which ensured both high fidelity and practicality for downstream applications. By utilizing MSAD-Net-assisted imaging, we characterize the biological morphology and functionality of muscle regeneration processes through deep in vivo five-channel imaging under low excitation power and short scanning time, while maintaining a high signal-to-noise ratio (SNR) and excellent axial spatial resolution. Furthermore, we conducted high axial-resolution dynamic imaging of vascular microcirculation, macrophages, and ghost fibers. Our findings provide a deeper understanding of the mechanisms underlying muscle regeneration at the cellular and tissue levels.

PhotoniXVol. 6(1)
International Society for Optics and Photonics (US), Tianjin University (CN), Hefei University of Technology (CN), Wuhan National Laboratory for Optoelectronics (CN), Second Affiliated Hospital of Zhejiang University (CN), Zhejiang University-University of Edinburgh Institute (CN), New York University (US)
National Natural Science Foundation of China, Huazhong University of Science and Technology, Zhejiang University
Openalex Percentile: Top 75%
Muscle Physiology and Disorders
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