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

Area of Science:

• Computational imaging
• Microscopy
• Neuroscience

Background:

• Mask-based integrated microscopy offers 3D imaging in a compact device.
• Key challenges include maintaining reconstruction quality with 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, highly scalable reconstruction algorithm tailored for mask-based integrated microscopy.
• Joint optimization of hardware components and computational reconstruction techniques.
• Implementation of the DeepInMiniscope system for neural activity recording.

Main Results:

• Achieved high-quality 3D imaging over large volumes with reduced computational requirements.
• Demonstrated robust and efficient recording of neural activity in the mouse brain.
• Near-cellular resolution was attained in functional recordings.

Conclusions:

• DeepInMiniscope provides a breakthrough in computational imaging for large-scale 3D functional recording.
• The system is a significant step towards in vivo imaging in freely-behaving animals.
• This framework enhances the efficiency and quality of 3D microscopy for neuroscience research.