June 2015
Volume 56, Issue 7
Free
ARVO Annual Meeting Abstract  |   June 2015
3D Reconstruction of Ocular Structures with Quadroscopic Imaging Platform
Author Affiliations & Notes
  • Les Bogdanowicz
    Department of Bioengineering, University of Illinois at Chicago, Chicago, IL
  • John R Hetling
    Department of Bioengineering, University of Illinois at Chicago, Chicago, IL
    Ophthalmology and Visual Sciences, University of Illinois at Chicago, Chicago, IL
  • Footnotes
    Commercial Relationships Les Bogdanowicz, Ocumed (C); John Hetling, None
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science June 2015, Vol.56, 5257. doi:
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      Les Bogdanowicz, John R Hetling; 3D Reconstruction of Ocular Structures with Quadroscopic Imaging Platform. Invest. Ophthalmol. Vis. Sci. 2015;56(7 ):5257.

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

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Abstract

Purpose: There is a need to improve access to ophthalmic diagnostics in underserved populations, in particular for diagnosing and monitoring glaucomatous optic neuropathy. This study demonstrates proof of concept for a quadroscopic camera system utilizing smartphone-like cameras for volumetric imaging of the retinal surface.

Methods: Four high resolution cameras were arranged to image intersecting planes. A model eye with three-dimensional features for the optic nerve head and surrounding capillaries was designed in Siemens PLM CAD software and 3D printed on an Objet350V Pro printer using Verowhite. The lens is purchased from GWB International, it is an optically lumped single lens mydriatic eye model with a 6 mm pupil.<br /> The camera system is a four-angle fundus camera, modeled in Zemax and prototyped on an optical bench. The imaging system for each camera has three effective lenses: an objective creates an intermediate image of the retina, intermediate lenses to relay the image and compensate for defocus of the eye, and a final set of lenses to focus the image on the camera sensor. The cameras are mounted to a 3 inch plate yielding a seven degree angle relative to the optical center of the system.<br /> The cameras are 5MP Ximea MU9PM-MH subminiature USB 2.0 cameras. Cameras were calibrated for focus utilizing a calibration slide placed at the location of the retinal surface relative to the lens. Cameras were connected via USB to a computer and images were captured and processed in Matlab.<br /> The Matlab algorithm provides camera calibration, registration, depth recovery and 3D ocular image reconstructions from the quadroscopic image. The resulting reconstruction were compared to the known features in the Objet printed eye model.

Results: The algorithm calculated the height and depth of the optic nerve head, and geometry of the capillaries, with an initial accuracy of +/- 25 microns. This is lower resolution than provided by typical OCT systems, but sufficient to reveal clinically relevant changes in cup shape.

Conclusions: A quadroscopic camera system utilizing smartphone-like cameras for the reconstruction of 3D volumes of the retinal surface is feasible. The next phase of development will include evaluating the prototype system in human eyes for direct comparison to OCT. The ultimate vision for this technology is a low-cost, easily implemented diagnostic instrument to provide accurate volumetric imaging of the retinal surface.

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