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Computational high-resolution optical imaging of the living human retina

  • Nathan D. Shemonski
  • , Fredrick A. South
  • , Yuan Zhi Liu
  • , Steven G. Adie
  • , P. Scott Carney
  • , Stephen A. Boppart
  • University of Illinois at Urbana-Champaign
  • Cornell University

Research output: Contribution to journalArticlepeer-review

134 Scopus citations

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 structures. In ophthalmology, when combined with optical coherence tomography, HAO has enabled a detailed three-dimensional visualization of photoreceptor distributions and individual nerve fibre bundles 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.

Original languageEnglish
Pages (from-to)440-443
Number of pages4
JournalNature Photonics
Volume9
Issue number7
DOIs
StatePublished - Jun 30 2015

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