Investigative Ophthalmology & Visual Science Cover Image for Volume 61, Issue 7
June 2020
Volume 61, Issue 7
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ARVO Annual Meeting Abstract  |   June 2020
High-speed adaptive optics for imaging the living human eye with optical coherence tomography
Author Affiliations & Notes
  • Yan Liu
    School of Optometry, Indiana University, Bloomington, Indiana, United States
  • James A Crowell
    School of Optometry, Indiana University, Bloomington, Indiana, United States
  • Kazuhiro Kurokawa
    School of Optometry, Indiana University, Bloomington, Indiana, United States
  • Hae Won Jung
    School of Optometry, Indiana University, Bloomington, Indiana, United States
  • Marcel Trerice Bernucci
    School of Optometry, Indiana University, Bloomington, Indiana, United States
  • Donald Thomas Miller
    School of Optometry, Indiana University, Bloomington, Indiana, United States
  • Footnotes
    Commercial Relationships   Yan Liu, None; James Crowell, None; Kazuhiro Kurokawa, Indiana University (P); Hae Won Jung, None; Marcel Bernucci, None; Donald Miller, Indiana University (P)
  • Footnotes
    Support  NIH R01EY029808-01 and 5R01EY018339-12
Investigative Ophthalmology & Visual Science June 2020, Vol.61, 222. doi:
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      Yan Liu, James A Crowell, Kazuhiro Kurokawa, Hae Won Jung, Marcel Trerice Bernucci, Donald Thomas Miller; High-speed adaptive optics for imaging the living human eye with optical coherence tomography. Invest. Ophthalmol. Vis. Sci. 2020;61(7):222.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Adaptive optics (AO) measures and corrects ocular wavefront aberrations, enabling retinal imaging and stimulation at cellular resolution. Today, most closed-loop AO systems run at ≤15 Hz, resulting in slow (>1/3 sec) control loop convergence and wavefront correction. In addition, the low speeds prevent AO systems from fully correcting dynamic ocular aberrations, some of which change rapidly due to tear film disruptions and eye blinks. Here, we develop a much faster AO system and evaluate its use with optical coherence tomography (OCT).

Methods : Design of our high-speed AO system centers on (1) a fast Shack-Hartmann wavefront sensor (SHWS) with high spatial sampling and dynamic range and (2) highly efficient control software that minimizes data processing time. The SHWS comprises a 20 × 20 microlens array (pitch = 0.5 mm, f = 13.8 mm) and a high-speed streaming camera (Andor Zyla 5.5). The camera runs at 122 Hz when the area of interest covers a 10 mm beam diameter. Each lenslet’s Airy spot is sampled by 8 pixels across and the dynamic range of the SHWS is 16 mrad. We implemented the centroiding algorithm in C/C++ using 5 OpenMP threads. A direct slope reconstruction method and an integral controller scheme determined the voltages for a deformable mirror (DM, ALPAO DM97-15). A gain of 0.2 ensured stability. Our control software completes data processing in 3.5 ms, including unpacking the SHWS image, centroiding spots, detecting and handling of blink and bad spots, computing Zernike coefficients and RMS wavefront error, and generating voltage commands for the DM. A control display provides real-time feedback of major wavefront diagnostics.

Results : After AO activation, the RMS wavefront error from a living human eye (6.7 mm pupil) dropped from 2 µm to 0.06 µm (diffraction limit=λ/14=0.06 µm) within 90 ms (n=2), twice as fast as other high-speed AO systems reported in literature for a similar drop. After a blink, the RMS wavefront error dropped from >1.5 µm to 0.06 µm in 128±7 ms (n=5). The bandwidth of our AO system determined from a power rejection measurement is ~5 Hz, which is close to its theoretical value (4.4 Hz) obtained from a transfer function analysis. With OCT, we successfully resolved cone cells as close as 100 µm from the fovea.

Conclusions : We have developed, to our knowledge, the fastest AO system with high spatial sampling and combined it with OCT to image the living human retina.

This is a 2020 ARVO Annual Meeting abstract.

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