Abstract

In many optical imaging applications, it is necessary to overcome aberrations to obtain high-resolution images. Aberration correction can be performed by either physically modifying the optical wavefront using hardware components, or by modifying the wavefront during image reconstruction using computational imaging. Here we address a longstanding issue in computational imaging: photons that are not collected cannot be corrected. This severely restricts the applications of computational wavefront correction. Additionally, performance limitations of hardware wavefront correction leave many aberrations uncorrected. We combine hardware and computational correction to address the shortcomings of each method. Coherent optical backscattering data is collected using high-speed optical coherence tomography, with aberrations corrected at the time of acquisition using a wavefront sensor and deformable mirror to maximize photon collection. Remaining aberrations are corrected by digitally modifying the coherently-measured wavefront during imaging reconstruction. This strategy obtains high-resolution images with improved signal-to-noise ratio of in vivo human photoreceptor cells with more complete correction of ocular aberrations, and increased flexibility to image at multiple retinal depths, field locations, and time points. While our approach is not restricted to retinal imaging, this application is one of the most challenging for computational imaging due to the large aberrations of the dilated pupil, time-varying aberrations, and unavoidable eye motion. In contrast with previous computational imaging work, we have imaged single photoreceptors and their waveguide modes in fully dilated eyes with a single acquisition. Combined hardware and computational wavefront correction improves the image sharpness of existing adaptive optics systems, and broadens the potential applications of computational imaging methods.

© 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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2017 (3)

2016 (7)

P. Pande, Y.-Z. Liu, F. A. South, and S. A. Boppart, “Automated computational aberration correction method for broadband interferometric imaging techniques,” Opt. Lett. 41(14), 3324–3327 (2016).
[Crossref] [PubMed]

F. A. South, Y.-Z. Liu, P. S. Carney, and S. A. Boppart, “Computed optical interferometric imaging: Methods, achievements, and challenges,” IEEE J. Sel. Top. Quantum Electron. 22(3), 186–196 (2016).
[Crossref] [PubMed]

D. Hillmann, H. Spahr, C. Hain, H. Sudkamp, G. Franke, C. Pfäffle, C. Winter, and G. Hüttmann, “Aberration-free volumetric high-speed imaging of in vivo retina,” Sci. Rep. 6(1), 35209 (2016).
[Crossref] [PubMed]

J. G. Fujimoto and E. A. Swanson, “The development, commercialization, and impact of optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 57(9), OCT1–OCT13 (2016).
[Crossref] [PubMed]

R. S. Jonnal, O. P. Kocaoglu, R. J. Zawadzki, Z. Liu, D. T. Miller, and J. S. Werner, “A review of adaptive optics optical coherence tomography: technical advances, scientific applications, and the future,” Invest. Ophthalmol. Vis. Sci. 57(9), OCT51–OCT68 (2016).
[Crossref] [PubMed]

Z. Liu, O. P. Kocaoglu, and D. T. Miller, “3D imaging of retinal pigment epithelial cells in the living human retina,” Invest. Ophthalmol. Vis. Sci. 57(9), OCT533 (2016).
[Crossref] [PubMed]

H. Tang, J. A. Mulligan, G. R. Untracht, X. Zhang, and S. G. Adie, “GPU-based computational adaptive optics for volumetric optical coherence microscopy,” Proc. SPIE 9720, 97200O (2016).
[Crossref]

2015 (3)

2014 (8)

F. Felberer, J.-S. Kroisamer, B. Baumann, S. Zotter, U. Schmidt-Erfurth, C. K. Hitzenberger, and M. Pircher, “Adaptive optics SLO/OCT for 3D imaging of human photoreceptors in vivo,” Biomed. Opt. Express 5(2), 439–456 (2014).
[Crossref] [PubMed]

N. D. Shemonski, S. G. Adie, Y.-Z. Liu, F. A. South, P. S. Carney, and S. A. Boppart, “Stability in computed optical interferometric tomography (Part I): Stability requirements,” Opt. Express 22(16), 19183–19197 (2014).
[Crossref] [PubMed]

Y.-Z. Liu, N. D. Shemonski, S. G. Adie, A. Ahmad, A. J. Bower, P. S. Carney, and S. A. Boppart, “Computed optical interferometric tomography for high-speed volumetric cellular imaging,” Biomed. Opt. Express 5(9), 2988–3000 (2014).
[Crossref] [PubMed]

N. D. Shemonski, S. S. Ahn, Y.-Z. Liu, F. A. South, P. S. Carney, and S. A. Boppart, “Three-dimensional motion correction using speckle and phase for in vivo computed optical interferometric tomography,” Biomed. Opt. Express 5(12), 4131–4143 (2014).
[Crossref] [PubMed]

O. P. Kocaoglu, T. L. Turner, Z. Liu, and D. T. Miller, “Adaptive optics optical coherence tomography at 1 MHz,” Biomed. Opt. Express 5(12), 4186–4200 (2014).
[Crossref] [PubMed]

S. Jia, J. C. Vaughan, and X. Zhuang, “Isotropic three-dimensional super-resolution imaging with a self-bending point spread function,” Nat. Photonics 8(4), 302–306 (2014).
[Crossref] [PubMed]

T. Vettenburg, H. I. C. Dalgarno, J. Nylk, C. Coll-Lladó, D. E. K. Ferrier, T. Čižmár, F. J. Gunn-Moore, and K. Dholakia, “Light-sheet microscopy using an Airy beam,” Nat. Methods 11(5), 541–544 (2014).
[Crossref] [PubMed]

M. J. Booth, “Adaptive optical microscopy: the ongoing quest for a perfect image,” Light Sci. Appl. 3(4), e165 (2014).
[Crossref]

2013 (3)

2012 (6)

R. Davies and M. Kasper, “Adaptive optics for astronomy,” Annu. Rev. Astron. Astrophys. 50(1), 305–351 (2012).
[Crossref]

S. G. Adie, B. W. Graf, A. Ahmad, P. S. Carney, and S. A. Boppart, “Computational adaptive optics for broadband optical interferometric tomography of biological tissue,” Proc. Natl. Acad. Sci. U.S.A. 109(19), 7175–7180 (2012).
[Crossref] [PubMed]

S. Quirin, S. R. P. Pavani, and R. Piestun, “Optimal 3D single-molecule localization for superresolution microscopy with aberrations and engineered point spread functions,” Proc. Natl. Acad. Sci. U.S.A. 109(3), 675–679 (2012).
[Crossref] [PubMed]

R. S. Jonnal, O. P. Kocaoglu, Q. Wang, S. Lee, and D. T. Miller, “Phase-sensitive imaging of the outer retina using optical coherence tomography and adaptive optics,” Biomed. Opt. Express 3(1), 104–124 (2012).
[Crossref] [PubMed]

A. Facomprez, E. Beaurepaire, and D. Débarre, “Accuracy of correction in modal sensorless adaptive optics,” Opt. Express 20(3), 2598–2612 (2012).
[Crossref] [PubMed]

J. Zeng, P. Mahou, M.-C. Schanne-Klein, E. Beaurepaire, and D. Débarre, “3D resolved mapping of optical aberrations in thick tissues,” Biomed. Opt. Express 3(8), 1898–1913 (2012).
[Crossref] [PubMed]

2011 (1)

2008 (3)

M. Guizar-Sicairos, S. T. Thurman, and J. R. Fienup, “Efficient subpixel image registration algorithms,” Opt. Lett. 33(2), 156–158 (2008).
[Crossref] [PubMed]

P. Bedggood, M. Daaboul, R. Ashman, G. Smith, and A. Metha, “Characteristics of the human isoplanatic patch and implications for adaptive optics retinal imaging,” J. Biomed. Opt. 13(2), 024008 (2008).
[Crossref] [PubMed]

B. Huang, W. Wang, M. Bates, and X. Zhuang, “Three-dimensional super-resolution imaging by stochastic optical reconstruction microscopy,” Science 319(5864), 810–813 (2008).
[Crossref] [PubMed]

2007 (2)

2006 (1)

2004 (1)

2001 (1)

2000 (1)

1997 (1)

1995 (1)

1993 (1)

J. M. Beckers, “Adaptive optics for astronomy: Principles, performance, and applications,” Annu. Rev. Astron. Astrophys. 31(1), 13–62 (1993).
[Crossref]

1991 (2)

D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991).
[Crossref] [PubMed]

M. Gu, C. J. R. Sheppard, and X. Gan, “Image formation in a fiber-optical confocal scanning microscope,” J. Opt. Soc. Am. A 8(11), 1755–1761 (1991).
[Crossref]

1990 (1)

C. A. Curcio, K. R. Sloan, R. E. Kalina, and A. E. Hendrickson, “Human photoreceptor topography,” J. Comp. Neurol. 292(4), 497–523 (1990).
[Crossref] [PubMed]

1986 (1)

Adie, S. G.

H. Tang, J. A. Mulligan, G. R. Untracht, X. Zhang, and S. G. Adie, “GPU-based computational adaptive optics for volumetric optical coherence microscopy,” Proc. SPIE 9720, 97200O (2016).
[Crossref]

N. D. Shemonski, F. A. South, Y.-Z. Liu, S. G. Adie, P. S. Carney, and S. A. Boppart, “Computational high-resolution optical imaging of the living human retina,” Nat. Photonics 9(7), 440–443 (2015).
[Crossref] [PubMed]

N. D. Shemonski, S. G. Adie, Y.-Z. Liu, F. A. South, P. S. Carney, and S. A. Boppart, “Stability in computed optical interferometric tomography (Part I): Stability requirements,” Opt. Express 22(16), 19183–19197 (2014).
[Crossref] [PubMed]

Y.-Z. Liu, N. D. Shemonski, S. G. Adie, A. Ahmad, A. J. Bower, P. S. Carney, and S. A. Boppart, “Computed optical interferometric tomography for high-speed volumetric cellular imaging,” Biomed. Opt. Express 5(9), 2988–3000 (2014).
[Crossref] [PubMed]

S. G. Adie, B. W. Graf, A. Ahmad, P. S. Carney, and S. A. Boppart, “Computational adaptive optics for broadband optical interferometric tomography of biological tissue,” Proc. Natl. Acad. Sci. U.S.A. 109(19), 7175–7180 (2012).
[Crossref] [PubMed]

Ahmad, A.

Y.-Z. Liu, N. D. Shemonski, S. G. Adie, A. Ahmad, A. J. Bower, P. S. Carney, and S. A. Boppart, “Computed optical interferometric tomography for high-speed volumetric cellular imaging,” Biomed. Opt. Express 5(9), 2988–3000 (2014).
[Crossref] [PubMed]

S. G. Adie, B. W. Graf, A. Ahmad, P. S. Carney, and S. A. Boppart, “Computational adaptive optics for broadband optical interferometric tomography of biological tissue,” Proc. Natl. Acad. Sci. U.S.A. 109(19), 7175–7180 (2012).
[Crossref] [PubMed]

Ahn, S. S.

Aragón, J. L.

Artal, P.

Ashman, R.

P. Bedggood, M. Daaboul, R. Ashman, G. Smith, and A. Metha, “Characteristics of the human isoplanatic patch and implications for adaptive optics retinal imaging,” J. Biomed. Opt. 13(2), 024008 (2008).
[Crossref] [PubMed]

Bates, M.

B. Huang, W. Wang, M. Bates, and X. Zhuang, “Three-dimensional super-resolution imaging by stochastic optical reconstruction microscopy,” Science 319(5864), 810–813 (2008).
[Crossref] [PubMed]

Baumann, B.

Beaurepaire, E.

Beckers, J. M.

J. M. Beckers, “Adaptive optics for astronomy: Principles, performance, and applications,” Annu. Rev. Astron. Astrophys. 31(1), 13–62 (1993).
[Crossref]

Bedggood, P.

P. Bedggood, M. Daaboul, R. Ashman, G. Smith, and A. Metha, “Characteristics of the human isoplanatic patch and implications for adaptive optics retinal imaging,” J. Biomed. Opt. 13(2), 024008 (2008).
[Crossref] [PubMed]

Booth, M. J.

M. J. Booth, “Adaptive optical microscopy: the ongoing quest for a perfect image,” Light Sci. Appl. 3(4), e165 (2014).
[Crossref]

S. A. Rahman and M. J. Booth, “Direct wavefront sensing in adaptive optical microscopy using backscattered light,” Appl. Opt. 52(22), 5523–5532 (2013).
[Crossref] [PubMed]

Boppart, S. A.

Y.-Z. Liu, F. A. South, Y. Xu, P. S. Carney, and S. A. Boppart, “Computational optical coherence tomography [Invited],” Biomed. Opt. Express 8(3), 1549–1574 (2017).
[Crossref] [PubMed]

F. A. South, Y.-Z. Liu, P. S. Carney, and S. A. Boppart, “Computed optical interferometric imaging: Methods, achievements, and challenges,” IEEE J. Sel. Top. Quantum Electron. 22(3), 186–196 (2016).
[Crossref] [PubMed]

P. Pande, Y.-Z. Liu, F. A. South, and S. A. Boppart, “Automated computational aberration correction method for broadband interferometric imaging techniques,” Opt. Lett. 41(14), 3324–3327 (2016).
[Crossref] [PubMed]

N. D. Shemonski, F. A. South, Y.-Z. Liu, S. G. Adie, P. S. Carney, and S. A. Boppart, “Computational high-resolution optical imaging of the living human retina,” Nat. Photonics 9(7), 440–443 (2015).
[Crossref] [PubMed]

N. D. Shemonski, S. G. Adie, Y.-Z. Liu, F. A. South, P. S. Carney, and S. A. Boppart, “Stability in computed optical interferometric tomography (Part I): Stability requirements,” Opt. Express 22(16), 19183–19197 (2014).
[Crossref] [PubMed]

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Y.-Z. Liu, F. A. South, Y. Xu, P. S. Carney, and S. A. Boppart, “Computational optical coherence tomography [Invited],” Biomed. Opt. Express 8(3), 1549–1574 (2017).
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F. A. South, Y.-Z. Liu, P. S. Carney, and S. A. Boppart, “Computed optical interferometric imaging: Methods, achievements, and challenges,” IEEE J. Sel. Top. Quantum Electron. 22(3), 186–196 (2016).
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N. D. Shemonski, S. G. Adie, Y.-Z. Liu, F. A. South, P. S. Carney, and S. A. Boppart, “Stability in computed optical interferometric tomography (Part I): Stability requirements,” Opt. Express 22(16), 19183–19197 (2014).
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Y.-Z. Liu, N. D. Shemonski, S. G. Adie, A. Ahmad, A. J. Bower, P. S. Carney, and S. A. Boppart, “Computed optical interferometric tomography for high-speed volumetric cellular imaging,” Biomed. Opt. Express 5(9), 2988–3000 (2014).
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N. D. Shemonski, S. S. Ahn, Y.-Z. Liu, F. A. South, P. S. Carney, and S. A. Boppart, “Three-dimensional motion correction using speckle and phase for in vivo computed optical interferometric tomography,” Biomed. Opt. Express 5(12), 4131–4143 (2014).
[Crossref] [PubMed]

S. G. Adie, B. W. Graf, A. Ahmad, P. S. Carney, and S. A. Boppart, “Computational adaptive optics for broadband optical interferometric tomography of biological tissue,” Proc. Natl. Acad. Sci. U.S.A. 109(19), 7175–7180 (2012).
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D. Hillmann, H. Spahr, C. Hain, H. Sudkamp, G. Franke, C. Pfäffle, C. Winter, and G. Hüttmann, “Aberration-free volumetric high-speed imaging of in vivo retina,” Sci. Rep. 6(1), 35209 (2016).
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D. Hillmann, H. Spahr, C. Hain, H. Sudkamp, G. Franke, C. Pfäffle, C. Winter, and G. Hüttmann, “Aberration-free volumetric high-speed imaging of in vivo retina,” Sci. Rep. 6(1), 35209 (2016).
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Z. Liu, O. P. Kocaoglu, T. L. Turner, and D. T. Miller, “Modal content of living human cone photoreceptors,” Biomed. Opt. Express 6(9), 3378–3404 (2015).
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O. P. Kocaoglu, T. L. Turner, Z. Liu, and D. T. Miller, “Adaptive optics optical coherence tomography at 1 MHz,” Biomed. Opt. Express 5(12), 4186–4200 (2014).
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Z. Liu, O. P. Kocaoglu, and D. T. Miller, “In-the-plane design of an off-axis ophthalmic adaptive optics system using toroidal mirrors,” Biomed. Opt. Express 4(12), 3007–3029 (2013).
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R. S. Jonnal, O. P. Kocaoglu, Q. Wang, S. Lee, and D. T. Miller, “Phase-sensitive imaging of the outer retina using optical coherence tomography and adaptive optics,” Biomed. Opt. Express 3(1), 104–124 (2012).
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Y.-Z. Liu, F. A. South, Y. Xu, P. S. Carney, and S. A. Boppart, “Computational optical coherence tomography [Invited],” Biomed. Opt. Express 8(3), 1549–1574 (2017).
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F. A. South, Y.-Z. Liu, P. S. Carney, and S. A. Boppart, “Computed optical interferometric imaging: Methods, achievements, and challenges,” IEEE J. Sel. Top. Quantum Electron. 22(3), 186–196 (2016).
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R. S. Jonnal, O. P. Kocaoglu, R. J. Zawadzki, Z. Liu, D. T. Miller, and J. S. Werner, “A review of adaptive optics optical coherence tomography: technical advances, scientific applications, and the future,” Invest. Ophthalmol. Vis. Sci. 57(9), OCT51–OCT68 (2016).
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Z. Liu, O. P. Kocaoglu, and D. T. Miller, “3D imaging of retinal pigment epithelial cells in the living human retina,” Invest. Ophthalmol. Vis. Sci. 57(9), OCT533 (2016).
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R. S. Jonnal, O. P. Kocaoglu, Q. Wang, S. Lee, and D. T. Miller, “Phase-sensitive imaging of the outer retina using optical coherence tomography and adaptive optics,” Biomed. Opt. Express 3(1), 104–124 (2012).
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H. Tang, J. A. Mulligan, G. R. Untracht, X. Zhang, and S. G. Adie, “GPU-based computational adaptive optics for volumetric optical coherence microscopy,” Proc. SPIE 9720, 97200O (2016).
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D. Hillmann, H. Spahr, C. Hain, H. Sudkamp, G. Franke, C. Pfäffle, C. Winter, and G. Hüttmann, “Aberration-free volumetric high-speed imaging of in vivo retina,” Sci. Rep. 6(1), 35209 (2016).
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S. Quirin, S. R. P. Pavani, and R. Piestun, “Optimal 3D single-molecule localization for superresolution microscopy with aberrations and engineered point spread functions,” Proc. Natl. Acad. Sci. U.S.A. 109(3), 675–679 (2012).
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D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991).
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S. Quirin, S. R. P. Pavani, and R. Piestun, “Optimal 3D single-molecule localization for superresolution microscopy with aberrations and engineered point spread functions,” Proc. Natl. Acad. Sci. U.S.A. 109(3), 675–679 (2012).
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D. Huang, E. A. Swanson, C. P. Lin, J. S. Schuman, W. G. Stinson, W. Chang, M. R. Hee, T. Flotte, K. Gregory, C. A. Puliafito, and J. G. Fujimoto, “Optical coherence tomography,” Science 254(5035), 1178–1181 (1991).
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B. A. Shafer, J. E. Kriske, O. P. Kocaoglu, T. L. Turner, Z. Liu, J. J. Lee, and D. T. Miller, “Adaptive-optics optical coherence tomography processing using a graphics processing unit,” 36th Ann Int Conf IEEE Eng. Med. Biol. Soc.3877–3880 (2014).
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Spahr, H.

D. Hillmann, H. Spahr, C. Hain, H. Sudkamp, G. Franke, C. Pfäffle, C. Winter, and G. Hüttmann, “Aberration-free volumetric high-speed imaging of in vivo retina,” Sci. Rep. 6(1), 35209 (2016).
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D. Hillmann, H. Spahr, C. Hain, H. Sudkamp, G. Franke, C. Pfäffle, C. Winter, and G. Hüttmann, “Aberration-free volumetric high-speed imaging of in vivo retina,” Sci. Rep. 6(1), 35209 (2016).
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J. G. Fujimoto and E. A. Swanson, “The development, commercialization, and impact of optical coherence tomography,” Invest. Ophthalmol. Vis. Sci. 57(9), OCT1–OCT13 (2016).
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Supplementary Material (2)

NameDescription
» Visualization 1       Cone photoreceptor mosaic before and after CAO wavefront correction. Subject 1.
» Visualization 2       Cone photoreceptor mosaic before and after CAO wavefront correction. Subject 2.

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Figures (6)

Fig. 1
Fig. 1 (a) Illustration of the CAO processing method on a human subject. Each depth plane in the retina is optimized independently using an aberration phase filter in the spatial frequency domain. (b) Depth planes corresponding to the photoreceptor reflections are extracted from the HAO and HAO + CAO volumes for comparison. Cross-sectional and depth-profile projections are shown to illustrate this process, where extracted depth layers are used to generate the cone and rod mosaics. IS/OS: Inner segment/outer segment junction. COST: Cone outer segment tips. ROST: Rod outer segment tips. Scalebar is 20 µm.
Fig. 2
Fig. 2 Human photoreceptor imaging with and without wavefront correction. (a) Cone mosaic without hardware wavefront correction. CAO corrects the ocular aberrations but cannot recover lost photons. (b) Cone mosaic with hardware wavefront correction. Photon collection is improved by HAO, and remaining aberrations are corrected using CAO. All images are displayed on a common amplitude scale to highlight differences in signal level. The peak SNR is given in decibels. Data taken at 12.5° temporal to the fovea in Subject 2. Scalebar is 20 µm.
Fig. 3
Fig. 3 HAO + CAO cone photoreceptor mosaic over 0.4° x 0.5° field-of-view at multiple retinal eccentricities. The top of each image is toward the fovea (nasal direction), and the fast-scanning axis is along the vertical dimension. Zoomed images correspond to the boxed areas in the cone mosaics. Signal traces are taken through the red lines in the zoomed images. Plots indicate the corresponding HAO (blue) and HAO + CAO (red) signals, with HAO + CAO showing an improved resolution. Scalebar is 20 µm. (See Visualization 1 and Visualization 2 for comparison across the full field-of-view.)
Fig. 4
Fig. 4 (a, d) HAO + CAO rod photoreceptor mosaic taken at 12.5° temporal to the fovea. Zoomed images correspond to boxed areas of corresponding color in the mosaic. Multiple individual rod photoreceptors can be resolved in the HAO + CAO data. (b, e) Dark patches in the rod mosaic correspond to pseudo-shadows of the cone photoreceptors, demonstrated by presenting the COST in magenta overlay. (c, f) Signal traces through the rod photoreceptors indicated by the white arrows in (a, d). Scalebar is 20 µm.
Fig. 5
Fig. 5 Cone photoreceptors at the same location imaged across multiple time-points and the corresponding CAO residual aberration corrections. The optimized CAO Zernike weights (numbered per the ANSI Z80.28 standard [45]) are shown for each time-point, along with the CAO phase filter (without defocus for improved visualization). A single photoreceptor is encircled to aid the reader in tracking the photoreceptor mosaic over time. Data taken at 3.5° temporal to the fovea in Subject 2. Scalebar is 20 µm.
Fig. 6
Fig. 6 Manual and automated measurement of cone densities with and without CAO. The automated HAO + CAO count is closer to the manual count in each case, especially near to the fovea. Representative automated counting results show improved cone detection with HAO + CAO. Estimated cone locations are indicated by the yellow markers. Scalebar is 2 µm.

Tables (1)

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Table 1 Residual wavefront RMS as a fraction of wavelength (λ) and image sharpness improvement (%)

Equations (3)

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ϕ i ={ mean( ϕ i1 , ϕ i+1 ), if ( ϕ i ϕ i1 )( ϕ i+1 ϕ i )<0 and | ϕ i1 ϕ i+1 |<π ϕ i , otherwise .
x,y [ S(x,y) S * (x,y) ] 2 .
SNR peak =10 log 10 ( max [ S(x,y) S * (x,y) ] 2 σ noise 2 ).

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