A plug-and-play ROI imaging module and deep-learning denoising framework extend three-photon microscopy to 1.7 mm depth

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Authors: J H Su, Shoupei Liu, Shasha Yang, Yanfeng Zhu, Xinyang Gu, Yaoguang Zhao, Chenjie Li, Min Zhang, Antao Chen Antao Chen, H. B. Yu, Bo Li
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Abstract

Three-photon microscopy (3PM) has extended optical imaging beyond the reach of two-photon microscopy (2PM), but its practical depth remains far below theoretical predictions because of low photon efficiency and severe noise contamination. Here we present an integrated hardware and software solution that addresses these limitations. We developed a plug-and-play region-of-interest (ROI) imaging module that selectively excites neuron-occupied regions to improve power efficiency and reduce photothermal stress. The module incorporates frame-partitioned accumulative (FPA) imaging for high signal-to-noise ratio (SNR) structural acquisition, automated neuron segmentation, and motion-robust registration for stable recordings. Complementing this, OptiCal is a cascaded deep-learning framework that removes mixed noise including periodic, motion-induced, and random components. Together, these innovations enable high-fidelity imaging to 1.7 mm depth, extending the practical limit of 3PM by about 400 μm while maintaining low excitation power. Our results reveal reliable calcium activity and behavior-correlated dynamics in deep medial prefrontal cortex of awake mice.

Fields of Study & Subjects

Advanced Fluorescence Microscopy Techniques Neural dynamics and brain function Cell Image Analysis Techniques

Publication details

Journal / source
bioRxiv (Cold Spring Harbor Laboratory)
Publication date
2 January 2026
Document type
Preprint