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Diffuser-based computational imaging funduscope

Yunzhe Li, Gregory N. McKay, Nicholas J. Durr, and Lei Tian

Open Access Open Access

Abstract

Poor access to eye care is a major global challenge that could be ameliorated by low-cost, portable, and easy-to-use diagnostic technologies. Diffuser-based imaging has the potential to enable inexpensive, compact optical systems that can reconstruct a focused image of an object over a range of defocus errors. Here, we present a diffuser-based computational funduscope that reconstructs important clinical features of a model eye. Compared to existing diffuser-imager architectures, our system features an infinite-conjugate design by relaying the ocular lens onto the diffuser. This offers shift-invariance across a wide field-of-view (FOV) and an invariant magnification across an extended depth range. Experimentally, we demonstrate fundus image reconstruction over a 33° FOV and robustness to ±4D refractive error using a constant point-spread-function. Combined with diffuser-based wavefront sensing, this technology could enable combined ocular aberrometry and funduscopic screening through a single diffuser sensor.

© 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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Figures (6)
Fig. 1.
Fig. 1. Overview of the proposed diffuser ocular imaging workflow, including: (a) PSF calibration, (b) diffuser-image acquisition, and (c) imaging reconstruction. The PSF is a highly structured caustic pattern. During acquisition, the sensor captures a 2D image resulting from the PSF convolved with the remitted light of the fundus. A high-quality retinal image is reconstructed by solving a regularized deconvolution problem.

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Fig. 2.
Fig. 2. Zemax ray-tracing of the (a) imaging and (b) illumination paths of the diffuser imager. (a) The cornea image is relayed to the diffuser so that each point on the retina produces a shifted caustic PSF. (b) Ring LEDs are also relayed to the cornea to avoid central illumination and reduce specular reflection. The FOV of the system is currently limited by the numerical aperture of the illumination optics.

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Fig. 3.
Fig. 3. Experimental setup of the diffuser-based funduscope. (a) Overhead view of the imaging and illumination paths, (b) details of compact components including the LED ring, a pair of polarizers crossed between the LED array and diffuser, and the diffuser camera, (c) a 3D-printed cap to confine the divergence angle of the illumination, and (d) diffuser camera components including a 3D printed iris placed in front of the diffuser to limit the size of the PSF.

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Fig. 4.
Fig. 4. Experimental FOV characterization of the imaging path of our prototype by using a self-illuminated retina. The design in (a) provides $\sim 50^\circ$ FOV, as demonstrated on (b) a dot-array object and (c) a retinal object. The raw diffuser image acquired from each object is shown in the green-outlined inset. The direct reconstructed images in (b)(i) and (c)(i) and the ones with flat field post-correction in (b)(ii) and (c)(ii) are compared. Cutlines are compared between the flat-field corrected reconstruction and the displayed object. The PCC, SSIM, and PSNR of each reconstructed image are computed against the original displayed object.

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Fig. 5.
Fig. 5. Experimental FOV characterization of external illumination and imaging. (a) Test objects are printed on paper and placed at the focal plane of the simple model eye. The PSF used is the same as was acquired previously from the OLED screen. (b,c) Our design provides $\sim$ 33 $^\circ$ FOV, as demonstrated with (b) ruler patterns with both positive and negative contrast, and (c) a retinal image. All reconstructions are flat-field corrected. Cutlines of the raw images are shown to compare the measurement contrast from the positive and negative contrasted ruler patterns. Cutlines are compared between the reconstruction and the printed pattern. The PCC, SSIM, and PSNR of each reconstructed image are computed against the original printed pattern.

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Fig. 6.
Fig. 6. Diffuser imaging of a commercial model eye. (a) Left: The data acquisition and PSF calibration are individually performed on different setups. Right: The reconstruction from both the measurement and the PSF taken with no refractive error (0D). (b) The reconstruction results using fundus measurements under different refractive errors with a 0D PSF. (c) The reconstruction results of a 0D fundus measurement using aberrated PSFs. Cutlines are shown in each reconstructed images and demonstrate consistent contrast with different refractive errors or defocused PSFs.

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