Researchers from Howard Hughes Medical Institute and Coleman Technologies of Chadds Ford, Pennsylvania have been tackling the persistent problem of fuzzy images when using microscopy to look below the surface of tissue. To actively adjust microscope settings to the tissue through which light is passing, they have taken some lessons from astronomy where adaptive optics have been used for years. The idea is that if you can identify how light is modulated by the medium it’s passing through, you can effectively reverse that effect and get an image of what the target would look like if it wasn’t blocked by the medium.
Central to the technique is a liquid crystal “spatial light modulator,” which both measures and samples’ optical variations and then sculpts a wave of light into a shape that all but nullifies the sample’s own image-blurring inconsistencies.
With control algorithms devised by the researchers, the liquid crystal element specifies a sequence of illumination patterns that serially probe the deflections of incoming light rays in tens or even hundreds of specific regions of the sample by measuring the image displacements caused by such deflections. An algorithm then translates these measurements into control signals that transform the same liquid crystal component into a mask that tilts the light rays so they converge at a common point, thus negating the sample’s own optical aberrations.
So far the researchers have proven the principle by successfully imaging one-micron diameter spheres tucked underneath a 300-micron thick slice of mouse brain tissue and neurons up to 400-microns deep inside mouse brain tissue.
Press release: Borrowing from Astronomy to See Cells in a New Light…
Abstract in Nature Methods: Adaptive optics via pupil segmentation for high-resolution imaging in biological tissues
Image credit: sharkbait