Adaptive light-sheet microscopy for long-term, high-resolution imaging in living organisms

Area of Science:

• Biomedical Imaging
• Microscopy
• Optical Engineering

Background:

• Optimal light-sheet microscopy demands precise alignment of the light sheet and detection focal plane.
• Specimen optical properties vary in space and time, causing imaging plane mismatches.
• Existing methods struggle with dynamic changes in live biological samples.

Purpose of the Study:

• To develop an automated, adaptive imaging framework for light-sheet microscopy.
• To overcome limitations of static imaging in dynamic biological specimens.
• To enhance spatial resolution and signal quality in live imaging.

Main Methods:

• Integration of a multi-view light-sheet microscope with digital plane manipulation.
• Development of a real-time computational method for continuous spatial optimization.
• Application of the AutoPilot framework to developing zebrafish and Drosophila embryos.

Main Results:

• Achieved two to five-fold improvement in spatial resolution and signal strength.
• Recovered previously unresolved cellular and sub-cellular structures.
• Demonstrated robust adaptation to dynamic biological processes and morphogenetic changes.

Conclusions:

• The AutoPilot framework enables high-performance, adaptive light-sheet microscopy for live specimens.
• This method significantly improves imaging quality and biological insight.
• It is suitable for long-term studies of developmental processes and functional imaging.