Abstract

An ophthalmic adaptive optics (AO) imaging system is especially affected by pupil edge effects due to the higher noise and aberration level at the edge of the human pupil as well as the impact of head and eye motions on the pupil. In this paper, a two-step approach was proposed and implemented for reducing the edge effects and improving wavefront slope boundary condition. First, given an imaging pupil, a smaller size of sampling aperture can be adopted to avoid the noisy boundary slope data. To do this, we calibrated a set of influence matrices for different aperture sizes to accommodate pupil variations within the population. In step two, the slope data was extrapolated from the less noisy slope data inside the pupil towards the outside such that we had reasonable slope data over a larger aperture to stabilize the impact of eye pupil dynamics. This technique is applicable to any Neumann boundary-based active /adaptive modality but it is especially useful in the eye for improving AO retinal image quality where the boundary positions fluctuate.

© 2011 OSA

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References

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2011 (1)

2010 (2)

2009 (1)

2008 (1)

2007 (2)

2006 (1)

J. S. McLellan, P. M. Prieto, S. Marcos, and S. A. Burns, “Effects of interactions among wave aberrations on optical image quality,” Vision Res.46(18), 3009–3016 (2006).
[CrossRef] [PubMed]

2005 (1)

2003 (1)

2002 (1)

2001 (1)

2000 (2)

1999 (1)

E. Acosta, S. Rios, M. Soto, and V. V. Voitsekhovich, “Role of boundary measurements in curvature sensing,” Opt. Commun.169(1-6), 59–62 (1999).
[CrossRef]

1997 (1)

1995 (1)

I. W. Han, “New method for estimating wavefront from curvature signal by curve fitting,” Opt. Eng.34(4), 1232–1237 (1995).
[CrossRef]

1993 (1)

1991 (1)

1988 (1)

1983 (1)

1978 (1)

Acosta, E.

E. Acosta, S. Rios, M. Soto, and V. V. Voitsekhovich, “Role of boundary measurements in curvature sensing,” Opt. Commun.169(1-6), 59–62 (1999).
[CrossRef]

Brase, J. M.

Brown, J. M.

Burns, S. A.

Cense, B.

Chen, D. C.

Chen, L.

Choi, S. S.

Deng, C.

Ferguson, R. D.

Gao, W.

Gavel, D. T.

Greenaway, A. H.

Hammer, D. X.

Han, I. W.

I. W. Han, “New method for estimating wavefront from curvature signal by curve fitting,” Opt. Eng.34(4), 1232–1237 (1995).
[CrossRef]

Hofer, H.

Ivers, K. M.

Jones, S. M.

Jonnal, R. S.

Kocaoglu, O. P.

Koperda, E.

Li, C.

Liang, J.

Marcos, S.

J. S. McLellan, P. M. Prieto, S. Marcos, and S. A. Burns, “Effects of interactions among wave aberrations on optical image quality,” Vision Res.46(18), 3009–3016 (2006).
[CrossRef] [PubMed]

McLellan, J. S.

J. S. McLellan, P. M. Prieto, S. Marcos, and S. A. Burns, “Effects of interactions among wave aberrations on optical image quality,” Vision Res.46(18), 3009–3016 (2006).
[CrossRef] [PubMed]

Miller, D. T.

Mujat, M.

Noll, R. J.

Oliver, S. S.

Olivier, S. S.

Patel, A. H.

Porter, J.

Poyneer, L. A.

Prieto, P. M.

J. S. McLellan, P. M. Prieto, S. Marcos, and S. A. Burns, “Effects of interactions among wave aberrations on optical image quality,” Vision Res.46(18), 3009–3016 (2006).
[CrossRef] [PubMed]

Qi, X.

Queener, H.

Reed Teague, M.

Rios, S.

E. Acosta, S. Rios, M. Soto, and V. V. Voitsekhovich, “Role of boundary measurements in curvature sensing,” Opt. Commun.169(1-6), 59–62 (1999).
[CrossRef]

Roddier, C.

Roddier, F.

Rolland, J. P.

Silva, D. A.

Singer, B.

Soto, M.

E. Acosta, S. Rios, M. Soto, and V. V. Voitsekhovich, “Role of boundary measurements in curvature sensing,” Opt. Commun.169(1-6), 59–62 (1999).
[CrossRef]

Sredar, N.

Tyler, G. A.

Voitsekhovich, V. V.

E. Acosta, S. Rios, M. Soto, and V. V. Voitsekhovich, “Role of boundary measurements in curvature sensing,” Opt. Commun.169(1-6), 59–62 (1999).
[CrossRef]

Werner, J. S.

Williams, D. R.

Woods, S. C.

Yamauchi, Y.

Yoon, G.-Y.

Zawadzki, R. J.

Zhang, Z.

Zhong, Z.

Zou, W.

Appl. Opt. (3)

Biomed. Opt. Express (1)

J. Opt. Soc. Am. (2)

J. Opt. Soc. Am. A (9)

C. Roddier and F. Roddier, “Wave-front reconstruction from defocused images and the testing of ground-based optical telescopes,” J. Opt. Soc. Am. A10(11), 2277–2287 (1993).
[CrossRef]

G. A. Tyler, “Reconstruction and assessment of the least-squares and slope discrepancy components of the phase,” J. Opt. Soc. Am. A17(10), 1828–1839 (2000).
[CrossRef] [PubMed]

J. Liang, D. R. Williams, and D. T. Miller, “Supernormal vision and high-resolution retinal imaging through adaptive optics,” J. Opt. Soc. Am. A14(11), 2884–2892 (1997).
[CrossRef] [PubMed]

L. A. Poyneer, D. T. Gavel, and J. M. Brase, “Fast wave-front reconstruction in large adaptive optics systems with use of the Fourier transform,” J. Opt. Soc. Am. A19(10), 2100–2111 (2002).
[CrossRef] [PubMed]

S. C. Woods and A. H. Greenaway, “Wave-front sensing by use of a Green’s function solution to the intensity transport equation,” J. Opt. Soc. Am. A20(3), 508–512 (2003).
[CrossRef] [PubMed]

W. Zou and J. P. Rolland, “Iterative zonal wave-front estimation algorithm for optical testing with general-shaped pupils,” J. Opt. Soc. Am. A22(5), 938–951 (2005).
[CrossRef] [PubMed]

D. C. Chen, S. M. Jones, D. A. Silva, and S. S. Olivier, “High-resolution adaptive optics scanning laser ophthalmoscope with dual deformable mirrors,” J. Opt. Soc. Am. A24(5), 1305–1312 (2007).
[CrossRef]

R. J. Zawadzki, S. S. Choi, S. M. Jones, S. S. Oliver, and J. S. Werner, “Adaptive optics-optical coherence tomography: optimizing visualization of microscopic retinal structures in three dimensions,” J. Opt. Soc. Am. A24(5), 1373–1383 (2007).
[CrossRef] [PubMed]

R. D. Ferguson, Z. Zhong, D. X. Hammer, M. Mujat, A. H. Patel, C. Deng, W. Zou, and S. A. Burns, “Adaptive optics scanning laser ophthalmoscope with integrated wide-field retinal imaging and tracking,” J. Opt. Soc. Am. A27(11), A265–A277 (2010).
[CrossRef]

Opt. Commun. (1)

E. Acosta, S. Rios, M. Soto, and V. V. Voitsekhovich, “Role of boundary measurements in curvature sensing,” Opt. Commun.169(1-6), 59–62 (1999).
[CrossRef]

Opt. Eng. (1)

I. W. Han, “New method for estimating wavefront from curvature signal by curve fitting,” Opt. Eng.34(4), 1232–1237 (1995).
[CrossRef]

Opt. Express (3)

Opt. Lett. (1)

Vision Res. (1)

J. S. McLellan, P. M. Prieto, S. Marcos, and S. A. Burns, “Effects of interactions among wave aberrations on optical image quality,” Vision Res.46(18), 3009–3016 (2006).
[CrossRef] [PubMed]

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Figures (10)

Fig. 1
Fig. 1

Indiana wide field dual DM AOSLO system.

Fig. 2
Fig. 2

AO control with iterative boundary slope extrapolation. The four boxes in yellow are to show the AO inverse computation with boundary slope extrapolation.

Fig. 3
Fig. 3

Model eye images obtained when the eye pupil was Φ5.68mm (SH 16 × 16) and the sampling aperture was set to (a) 20 × 20 SH sampling grid (Φ7.2mm) and (b) 14 × 14 SH sampling grid (Φ5.0mm). (c) is their wavefront rms comparison. The image resolution is improved by shrinking the pupil to avoid the slope errors at the wavefront boundary. Wavefront control accuracies with/without pupil adjustment differ by more than two log units.

Fig. 4
Fig. 4

RMS comparisons for a model eye with a physical pupil size of Φ7.22mm. The sampling apertures were varying from Φ4.32mm to Φ8.0mm. RMS error increases only when the sampling aperture size was larger than the physical pupil size.

Fig. 5
Fig. 5

Optimizing the sampling aperture size for AO performance with an artificial eye. When the sampling aperture was smaller than the Φ6.84mm physical pupil (SH 19 × 19), the wavefront rms values were all very small (<0.03µm); however, among them the Φ6.48mm sampling aperture (SH 18 × 18) provided the brightest image.

Fig. 6
Fig. 6

Retinal images focused just below the nerve fiber layer (450 × 450 pixels) of subject S1 with sampling apertures of (a) Φ7.56 mm and (b) Φ5.4 mm, where the dilated pupil of subject S1 was Φ6.84mm. (c) Spectrum power comparison based on the images within the two 120 × 120 pixels red-frame windows. We can clearly see the image improvement by avoiding the boundary errors.

Fig. 7
Fig. 7

Optimizing the sampling aperture size for the AOSLO AO performance with subject S2. (a) Single frame retinal images with different sampling aperture sizes. (b) Plot of image intensity as a function of sampling aperture size. We can see that the optimal sampling aperture size was Φ6.48 mm, which was the maximum aperture immediately smaller than the Φ6.84 mm physical pupil.

Fig. 8
Fig. 8

AO performance with/without boundary slope extrapolation measured on our AOLSO tested with the artificial eye. The physical pupil size was Φ5.4mm (SH 15 × 15). The solid lines represent image intensity curves, and the dash lines are wavefront rms values. The slope extrapolation method can improve the wavefront boundary condition and thereby improve AO performance.

Fig. 9
Fig. 9

Experimental results with subject S2 (pupil size Φ6.5mm, SH 18 × 18). The blue curve represents image intensities obtained by AO imaging with the Φ6.12 mm sampling aperture (SH 17 × 17), while the red curve was the image intensity obtained with the boundary slope extrapolation algorithm (from the Φ6.5 mm pupil inscribed in the SH 18 × 18 grid to the Φ7.22 mm aperture inscribed in the SH 20 × 20 grid). The green curve shows the image intensity with the Φ7.22 mm sampling aperture (SH 20 × 20) without slope extrapolation. We can see that for a large SH grid (20 × 20) and a smaller eye pupil (Φ6.5mm), the AO control accuracy with slope extrapolation was higher than that without slope extrapolation, and it was more stable compared to the AO control using the optimal sampling aperture (SH 17 × 17). The large jumps in intensity arose from eye blinks.

Fig. 10
Fig. 10

Plot of wavefront rms as a function of sampling aperture size for different AO modes with an artificial eye (physical pupil size Φ7.22mm). “Mirao held+BMC” mode: The Mirao DM was initially used for correction to converge, then the Mirao mirror profile was held and wavefront correction switched to the BMC DM AO mode. The “BMC held+Mirao” mode was similar to the “Mirao held+BMC” mode except that its dual DM AO correction sequence was in the opposite order [18].

Tables (1)

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Table 1 SH sampling grid series and their corresponding pupil sizes

Equations (2)

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{ 2 W=f( x,y ) W n | Ω = g 0 ( x,y ) ( x,y ) Ω ¯ ,  
 W( r )= Ω G( r , r ') f( r ') d 2 r ' Ω G( r , r ') g 0 ( r ')d n ^ ',

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