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Computational high-resolution optical imaging of the living human retina

An Addendum to this article was published on 29 September 2015

This article has been updated

Abstract

High-resolution in vivo imaging is of great importance for the fields of biology and medicine. The introduction of hardware-based adaptive optics (HAO) has pushed the limits of optical imaging, enabling high-resolution near diffraction-limited imaging of previously unresolvable structures1,2. In ophthalmology, when combined with optical coherence tomography, HAO has enabled a detailed three-dimensional visualization of photoreceptor distributions3,4 and individual nerve fibre bundles5 in the living human retina. However, the introduction of HAO hardware and supporting software adds considerable complexity and cost to an imaging system, limiting the number of researchers and medical professionals who could benefit from the technology. Here we demonstrate a fully automated computational approach that enables high-resolution in vivo ophthalmic imaging without the need for HAO. The results demonstrate that computational methods in coherent microscopy are applicable in highly dynamic living systems.

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Figure 1: Computational aberration correction and imaging of the living human retina.
Figure 2: Computational wavefront correction.
Figure 3: Quantitative stability analysis and correction.

Change history

  • 10 September 2015

    The authors acknowledge that two highly relevant manuscripts should have been cited in this Letter: Meitav, N. & Ribak, E. N. Improving retinal image resolution with iterative weighted shift-and-add. J. Opt. Soc. Am. A 28, 1395–1402 (2011) Meitav, N. & Ribak, E. N. Estimation of the ocular point spread function by retina modeling. Opt Lett. 37, 1466–1468 (2012) These manuscripts report progress towards in vivo high-resolution retinal imaging without using hardware-based adaptive optics by averaging out high-order, temporally changing aberrations, and by applying various image filters to the intensity of backscattered optical signals..

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Acknowledgements

The authors thank D. Spillman and E. Chaney from the Beckman Institute for Advanced Science and Technology for their assistance with operations and human study protocol support, respectively. This research was supported in part by grants from the National Institutes of Health (NIBIB, 1 R01 EB013723, 1 R01 EB012479) and the National Science Foundation (CBET 14-45111).

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Authors and Affiliations

Authors

Contributions

N.D.S. constructed the optical system, collected data, analysed data and wrote the paper. F.A.S., Y-Z.L, and S.G.A. collected and analysed data, and assisted in writing the paper. P.S.C. contributed the theoretical and mathematical basis for these methods, reviewed and edited the manuscript, and helped obtain funding. S.A.B. conceived of the study, analysed the data, reviewed and edited the manuscript and helped obtain funding.

Corresponding author

Correspondence to Stephen A. Boppart.

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Competing interests

S.A.B. and P.S.C. are co-founders of Diagnostic Photonics, which is licensing intellectual property from the University of Illinois at Urbana-Champaign related to interferometric synthetic aperture microscopy. S.A.B. also receives royalties from the Massachusetts Institute of Technology for patents related to optical coherence tomography. S.G.A., P.S.C. and S.A.B. are listed as inventors on a patent application (application no. 20140050382) related to the work presented in this manuscript. All other authors have nothing to disclose.

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Supplementary information

10.1038/nrrheum.2015.85 (PDF 1540 kb)

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Shemonski, N., South, F., Liu, YZ. et al. Computational high-resolution optical imaging of the living human retina. Nature Photon 9, 440–443 (2015). https://doi.org/10.1038/nphoton.2015.102

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