Computational hyperspectral light-sheet microscopy

Area of Science:

• Biomedical Engineering
• Optical Microscopy
• Spectroscopy

Background:

• Traditional light-sheet microscopy offers optical sectioning but often lacks spectral resolution.
• Hyperspectral imaging provides detailed spectral information crucial for identifying multiple fluorophores and cellular components.
• Integrating hyperspectral capabilities into light-sheet microscopy presents a significant technical challenge.

Purpose of the Study:

• To design and demonstrate a computational light-sheet microscope capable of high spectral resolution hyperspectral imaging.
• To develop a novel method for acquiring the spatial dimension orthogonal to the spectrometer slit.
• To validate the system's performance using in vivo imaging of biological specimens.

Main Methods:

• Utilized a cylindrical lens to focus emitted fluorescence onto an imaging spectrometer's entrance slit.
• Employed structured light illumination patterns and computational image reconstruction to capture the orthogonal spatial dimension.
• Integrated a digital micromirror device (DMD) for beam shaping within a selective plane illumination microscopy (SPIM) setup.

Main Results:

• Successfully demonstrated the feasibility of the computational hyperspectral light-sheet microscope.
• Achieved high spectral resolution hyperspectral data acquisition.
• Reported initial in vivo imaging results in hydra specimens labeled with two distinct fluorophores.

Conclusions:

• The developed computational light-sheet microscope effectively integrates hyperspectral imaging capabilities.
• This technique allows for detailed spectral and spatial analysis of biological samples in vivo.
• The system shows promise for advancing live biological imaging and molecular analysis.