June 2020
Volume 61, Issue 7
Free
ARVO Annual Meeting Abstract  |   June 2020
Towards multi-modal aberrometry and fundus screening with diffuser-based computational imaging
Author Affiliations & Notes
  • Gregory McKay
    Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States
  • Yunzhe Li
    Biomedical Engineering, Boston University, Massachusetts, United States
  • Ahhyun Stephanie Nam
    PlenOptika, Boston, Massachusetts, United States
  • Shivang Dave
    PlenOptika, Boston, Massachusetts, United States
  • Lei Tian
    Biomedical Engineering, Boston University, Massachusetts, United States
  • Nicholas J. Durr
    Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States
  • Footnotes
    Commercial Relationships   Gregory McKay, Johns Hopkins University (P); Yunzhe Li, None; Ahhyun Nam, PlenOptika (E); Shivang Dave, PlenOptika (E); Lei Tian, None; Nicholas Durr, Johns Hopkins University (P), PlenOptika (I)
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2020, Vol.61, 1847. doi:
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    • Get Citation

      Gregory McKay, Yunzhe Li, Ahhyun Stephanie Nam, Shivang Dave, Lei Tian, Nicholas J. Durr; Towards multi-modal aberrometry and fundus screening with diffuser-based computational imaging. Invest. Ophthalmol. Vis. Sci. 2020;61(7):1847.

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

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Abstract

Purpose : We recently showed that autorefraction with a diffuser-based wavefront sensor provides advantages of lower-cost components and larger dynamic range when compared to a lenslet array. Aberrometry is performed by registering a calibration image of a flat wavefront to the response of an illumination point projected on the retina. Here we show that this concept also allows image reconstruction when the fundus is flood-illuminated.

Methods : Our diffuser-based computational imager consists of a 0.5 degree holographic diffuser placed approximately 6mm away from a 16-bit monochrome CMOS image sensor, and conjugate to a model eye lens (MEL). The model eye fundus is flood-illuminated by projecting an LED ring through a beamsplitter and relay lens system [Figure 1(a)]. Image reconstruction is achieved using Tikhonov regularized deconvolution using a calibration PSF [Figure 1(b)]. The FOV is measured using variable point source arrays placed at the back focal plane of the MEL. A numerical target is also reconstructed to explore subjective image quality [Figure 1(c)].

Results : We reconstruct an object with 30 degree FOV in a model eye in approximately 150ms [Figure 1(d)-(e)]. We observe the expected tradeoff between resolution, image signal to noise ratio (SNR), and FOV. Reconstruction quality improves with increased sparsity of the object. Decreasing the diffuser aperture size increases the FOV and decreases the SNR of our reconstructed image.

Conclusions : This proof-of-concept demonstrates that a diffuser camera can be used to reconstruct fundus images of a model eye using the same optical system as a diffuser-based autorefractor. The tools and expertise necessary for comprehensive eye examinations is a critical bottleneck to improving the accessibility of eye care in low- and middle-resource settings. This work may support the development of impactful technologies that enable combined ocular refraction and fundoscopic screening for abnormalities in a compact, low-cost device.

This is a 2020 ARVO Annual Meeting abstract.

 

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