Photonics Breakthroughs 2025: Mask-Based Integrated Miniscope for Large-scale Volumetric Imaging

Area of Science:

• Computational imaging
• Microscopy
• Neuroscience

Background:

• Mask-based integrated microscopy enables 3D imaging with a compact footprint.
• Key challenges include maintaining reconstruction quality at low signal-to-background ratios and reducing computational load for larger volumes.

Purpose of the Study:

• To introduce DeepInMiniscope, a novel system with a scalable reconstruction algorithm for high-quality, large-volume 3D imaging.
• To detail the integrated hardware and algorithm development for an efficient and robust imaging framework.

Main Methods:

• Development of a novel mask-based integrated microscopy system (DeepInMiniscope).
• Implementation of a highly scalable reconstruction algorithm tailored for large 3D volumes.
• Joint optimization of hardware and computational reconstruction for improved imaging performance.

Main Results:

• Achieved high-quality 3D imaging over large volumes with reduced computational requirements.
• Demonstrated the system's capability to record neural activity in the mouse brain at near-cellular resolution.
• Validated the efficiency and robustness of the DeepInMiniscope imaging framework.

Conclusions:

• DeepInMiniscope represents a significant advancement in mask-based integrated microscopy.
• The system facilitates large-scale, 3D functional neural recording in freely-behaving animals.
• This breakthrough enables more comprehensive studies of brain activity in vivo.