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Proceedings Paper

Full three-dimensional aberration-free super-resolution imaging through thick multicellular samples
Author(s): Ruizhe Lin; Peter A. Kner
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Paper Abstract

Structured illumination microscopy has been used with great success on single cell samples. However, it cannot be applied to multicellular thick samples because aberrations caused by the sample not only reduce the intrinsic resolution and contrast, they cause the SIM reconstruction to fail. Although the structured illumination pattern can still be projected onto the focal plane inside the sample when imaging deep into thick biological samples, the resulting raw fluorescent images are corrupted resulting in poor reconstructed SIM images with poor signal to noise ratio, degraded spatial resolution and artifacts that can call into question the reliability of the image. To image in thicker samples with diffraction limited resolution, adaptive optics can be used to correct the optical aberrations due to the sample. Here, we combine three-dimensional structured illumination microscopy (3DSIM) and adaptive optics (AO), demonstrating full three-dimensional aberration-free super-resolution imaging deep into thick multicellular samples. We applied a frequency-based metric function in image-based sensorless AO method for aberration corrections. In some cases, we also applied a customized dot-array illumination pattern to optimize the image spectrum. Through the imaging of various samples, we show that the image-based sensorless AO method performs a satisfying and robust correction of different aberrations with minimal photobleaching. The final three-dimensional image achieves a resolution of ~120 nm laterally and ~500 nm axially with optical sectioning, which is a two-fold resolution enhancement without any nonlinear deconvolution methods. AO-3DSIM provides a reliable solution for three-dimensional super-resolution imaging in vivo with improved fidelity.

Paper Details

Date Published: 17 February 2020
PDF: 6 pages
Proc. SPIE 11248, Adaptive Optics and Wavefront Control for Biological Systems VI, 112480D (17 February 2020); doi: 10.1117/12.2544378
Show Author Affiliations
Ruizhe Lin, The Univ. of Georgia (United States)
Peter A. Kner, The Univ. of Georgia (United States)


Published in SPIE Proceedings Vol. 11248:
Adaptive Optics and Wavefront Control for Biological Systems VI
Thomas G. Bifano; Sylvain Gigan; Na Ji, Editor(s)

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