Biological specimens are rife with optical inhomogeneities that seriously degrade imaging performance under all but the most ideal conditions. Measuring and then correcting for these inhomogeneities is the province of adaptive optics. Here we introduce an approach to adaptive optics in microscopy wherein the rear pupil of an objective lens is segmented into subregions, and light is directed individually to each subregion to measure, by image shift, the deflection faced by each group of rays as they emerge from the objective and travel through the specimen toward the focus. Applying our method to two-photon microscopy, we could recover near-diffraction–limited performance from a variety of biological and nonbiological samples exhibiting aberrations large or small and smoothly varying or abruptly changing. In particular, results from fixed mouse cortical slices illustrate our ability to improve signal and resolution to depths of 400 μm.
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We thank our colleagues at Janelia Farm Research Campus, Howard Hughes Medical Institute, B. Shields, A. Hu, W. Amir, R. Kerr, J. Truman, M. Hooks andJ. Makara for help with sample preparation, J. Osborne and S. Bassin for help with machining and T. Sato and T. Planchon for helpful discussions.
The authors declare no competing financial interests.
Supplementary Figures 1–18 (PDF 8285 kb)
Spatial light modulator patterns (right) and resulting images (left) acquired during implementation of our pupil segmentation based AO algorithm with independent subregion masks and direct phase measurement. (AVI 3930 kb)
Rotating three-dimensional view of integrated intensity projections from a field of 500-nm-diameter fluorescent beads in water before (4× display gain) and after correction for system aberration. (AVI 1858 kb)
Rotating three-dimensional view of integrated intensity projections from a field of 500-nm-diameter fluorescent beads in air before (7× display gain) and after AO correction. (AVI 4439 kb)
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Ji, N., Milkie, D. & Betzig, E. Adaptive optics via pupil segmentation for high-resolution imaging in biological tissues. Nat Methods 7, 141–147 (2010). https://doi.org/10.1038/nmeth.1411
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